Texture Contrast Research Articles

Contrapartes

Contrapartes Ivonne Hernández (bio) Performance Notes Contrapartes Counterparts En mi cuerpo buscas la montaña. In my body you search the mountain. Por el sol enterrado en su bosque. For the sun buried in its forest. En tu cuerpo busco el barco. In your body I search for the boat. A la deriva en medio de la noche. Adrift in the middle of the night. Basado en el poema Based on the poem “Complementarios” de Octavio Paz “Complementarios” by Octavio Paz Notational Note indicated by a triangle should have more air than pitch Brackets designate duration (as indicated by the time marking) Arrows indicate a slow, airy transition between two types of sounds Whistle tones; pitch is approximate Multiphonics; fingerings are indicated under the staff [End Page 184] Click for larger view View full resolution [End Page 186] Click for larger view View full resolution [End Page 187] Ivonne Hernández ivonne hernández (b. Mexico, 1998) is a Mexican composer. She began her studies in music in 2010 at the State School of Fine Arts of Nayarit. In 2016 she enrolled at the Conservatorio de las Rosas. Her music is characterized by the search for musical narratives from the exploration of atmospheric sounds, the contrast of textures, and timbral appreciations. She has premiered several contemporary works in different concert seasons at the Conservatorio de las Rosas. She has also had several presentations in Morelia (Mexico), at the Festival Zeppelin 2018 in Barcelona (Spain), and with Ecco Chamber Ensemble in Seattle, Washington (the United States). Nowadays she is working toward a bachelor of music under the tutelage of Dr. Juan Sebastián Lach. Copyright © 2019 Suzanne G. Cusick

An Optimal Long-Term Aerial Infrared Object Tracking Algorithm With Re-Detection

In the field of automatic target recognition and tracking, long-term tracking for aerial infrared target has been recently seen with great interest. Although deep trackers and correlation filtering trackers offer competitive results on performance, the problems of deformation, abrupt motion, heavy occlusion, and out of view still remain unsolved. In addition, since this paper focus on infrared images, it is also important to consider that infrared images have a significant drawbacks, such as low resolution, low contrast, and lack of textures. In this paper, we adopt correlation filtering trackers and deep learning detection method to achieve accurate tracking results. Our tracking system composed of three parts: the DTB correlation filtering tracker (DTB-CF), a better regression model to discriminate the target from the background with adjustable Gaussian window functions; the UTA correlation filtering tracker (UTA-CF), an optimum regression model to update the target appearance with simultaneously optimal in position, scale, and integration of multi-feature fusion; and the YOLOv3 re-detector, which ensures re-location of the correct position of the target when the tracking fails. In addition, we introduce the ratio between average peak-to-correlation energy (APCE) of the current frame and average APCE of former frames as a criterion to update the UTA-CF tracker to maintain the target model stability. And we combine the nearest neighbor maximum value method with APCE as criterion together to initialize the YOLOv3 re-detector. We evaluate our algorithm on real aerial infrared target thermal image sequences in terms of precision plot, success plot, and speed. The experimental results show that our method has a significant improvement than the state-of-the-art methods for long-term tracking both in accuracy and robustness for aerial infrared object tracking.

RHETORICAL FIGURE ANTITHETON IN THE CHORAL CONCERT “I BLESS THE LORD” OF IVAN DOMARATS’KYJ

The main objective of the article is to present the contrast in Ukrainian baroque choral music in a new aspect that is in its rhetorical meaning. It stands to reason that the contrast is the main structure-building component in Ukrainian choral compositions of that period. Nevertheless, its function might get a new meaning in the light of the rhetorical approach. Methodology. Both methods of analysis and synthesis were performed to give an account of rhetorical function of contrast in certain elements of musical language, such as melody, modus, texture, range, and also to systematize the most common semantic meaning in each type of contrast. The method of hermeneutic analysis was conducted in order to apply more complex approach to the study. In this regard analysis comprised study of the text semantics and its correlation with music, as well as implementation of means used in western-European researches. Relevance of the study. Such rhetorical approach is a pre-requisite for rhetorical performance, which is also called historically informed performance. Rhetorical performance has to build its expressiveness on the basis of rhetorical means in the musical texture that is rhetorical figures. This practice is now commonly implied, although it’s still on the stage of developing the theoretical basis in Ukrainian musicology. Findings. In this paper was revealed that I. Domarats’kyj more frequently implied two types of rhetorical figure antitheton, namely contradiction in modus and in texture. The semantic of modus contrast is represented in three different ways: as musical emphasis, as embodiment of certain images, as structural component. The semantic of textural contrast often mirrors juxtaposition in quantities in literary text while the range contrast reflects two different images or aesthetic categories, like good and evil.

Soil carbon sequestration to depth in response to long-term phosphorus fertilization of grazed pasture

The impact of phosphorus (P) fertilizer application on the sequestration of soil organic carbon (C) was investigated in an acidic permanent pasture soil grazed by sheep. Data were collected after 20 years of P fertilization (average 19 kg P ha−1 year−1) compared to a non-P fertilized control, on a P deficient soil. The high P treatment had higher productivity and stocking rate (hereafter termed fertilization treatment). Soils to a depth of 110 cm were analysed for soil bulk density, whole soil C and nitrogen (N), and for C, N, P and sulphur (S) that was associated with a soil pool of fine fraction C (FFC). Fertilization and higher stocking rate had no effect on soil pH but led to a decrease in soil bulk density to depth, and an increase in total soil C that was associated with an increase in both the whole soil C (WSC) and the FFC throughout much of the soil profile. The increase in soil C was evident in both the C concentration (mg C kg−1 soil) and C stocks (Mg C ha−1) to a depth of at least 60 cm, with the largest difference between fertilizer treatments occurring in the top 10 cm soil layer. In the 0–10 cm layer, P fertilization increased soil organic matter (SOM) by ~1% from 3% SOM in the unfertilized treatment to 4% SOM in the fertilized treatment. Over the top 60 cm of soil profile, P fertilization increased total C stock by 12 Mg C ha−1, with 92% of the C stock associated with the FFC. The higher soil C in the fertilized treatment was also correlated with a concomitant increase in N, P and S content in the FFC pool (R2 = 0.97, 0.89 to 0.82 for N, P and S, respectively), whereas in the unfertilized treatment nutrient correlations with C in the FFS were observed for N and S only. Although C:N, C:P and C:S nutrient mass ratios in the FFC pool differed markedly with soil depth, no significant difference in nutrient ratios were observed due to fertilizer treatment for any of the nutrients. Collectively our data indicate that sustained P input to a texture contrast pasture soil (Yellow Chromosol) and its associated increase in stocking rate and productivity in a temperate climate had significant long-term benefit for C sequestration and accumulation of soil organic matter (SOM) throughout the soil profile.

Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging study

BackgroundMulti-site neuroimaging offer several benefits and poses tough challenges in the drug development process. Although MRI protocol and clinical guidelines developed to address these challenges recommend the use of good quality images, reliable assessment of image quality is hampered by the several shortcomings of existing techniques.MethodsGiven a test image two feature images are extracted. They are grayscale and contrast feature images. Four binary images are generated by setting four different global thresholds on the feature images. Image quality is predicted by measuring the structural similarity between appropriate pairs of binary images. The lower and upper limits of the quality index are 0 and 1. Quality prediction is based on four quality attributes; luminance contrast, texture, texture contrast and lightness.ResultsPerformance evaluation on test data from three multi-site clinical trials show good objective quality evaluation across MRI sequences, levels of distortion and quality attributes. Correlation with subjective evaluation by human observers is ≥ 0.6.ConclusionThe results are promising for the evaluation of MRI protocols, specifically the standardization of quality index, designed to overcome the challenges encountered in multi-site clinical trials.

A quantified study of segmentation techniques on synthetic geological XRM and FIB-SEM images

Three sets of synthetic images were created from two original datasets. A suite exhibiting greyscale contrast was produced from an 8.96-μm voxel size 3D X-ray microscopy image of a sandstone rock and a two suites (one showing greyscale contrast and one showing both greyscale and textural contrast) were produced from a 5 × 5 × 5 nm voxel size FIB-SEM image of a shale rock. The performance of three image segmentation algorithms (global multi-Otsu thresholding, seeded watershed region growing, and machine learning-based multivariant classification) was then assessed by their ability to recover their respective original segmented 3D images. While all algorithms performed well at low noise levels, machine learning-based classification proved significantly more noise tolerant than either of the traditional algorithms. It was also able to segment the non-greyscale (textural based) contrast, something the traditional completely failed to do, with voxel misclassification rates for the traditional techniques above 50% at a 0 noise level within the textural contrast regions. Machine learning-based classification, in contrast, achieved misclassification rates of less than 5% in the same regions.

Enhancing Motion-In-Depth Perception of Random-Dot Stereograms.

Random-dot stereograms have been widely used to explore the neural mechanisms underlying binocular vision. Although they are a powerful tool to stimulate motion-in-depth (MID) perception, published results report some difficulties in the capacity to perceive MID generated by random-dot stereograms. The purpose of this study was to investigate whether the performance of MID perception could be improved using an appropriate stimulus design. Sixteen inexperienced observers participated in the experiment. A training session was carried out to improve the accuracy of MID detection before the experiment. Four aspects of stimulus design were investigated: presence of a static reference, background texture, relative disparity, and stimulus contrast. Participants' performance in MID direction discrimination was recorded and compared to evaluate whether varying these factors helped MID perception. Results showed that only the presence of background texture had a significant effect on MID direction perception. This study provides suggestions for the design of 3D stimuli in order to facilitate MID perception.

A novel adaptive fast partition algorithm based on CU complexity analysis in HEVC

High efficiency video coding (HEVC) is the latest video coding standard. Compared with H.264, the proposal of quad-tree structure not only improves the coding efficiency greatly but also increases complexity of coding. Therefore, this paper performed a fast-adaptive algorithm based on the complexity of images for intra prediction. Two values from micro and macro levels are considered for each coding unit block. We use entropy on the macroscopic level and texture contrast on the microscopic level. Relatively, large pictures always have more smooth blocks and there are more complex blocks in small pictures. To deal with this problem, this study uses adaptive process to make the values of entropy and texture contrast close to the ideal values of the current video, thereby making the division reasonable. Experimental results show that the proposed algorithm can reduce 34.6% coding time on average, with a loss of Bjontegaard delta rate of 0.8%.

Effect of mechanical contrast on sensory perception of heterogeneous liquid and semi-solid foods

This study investigated the influence of size and fracture stress (σF) of dispersed particles embedded in liquid and semi-solid model food matrices on sensory perception and hedonic response. К-carrageenan particles varying in size (0.8, 2.4, 4.2 mm) and fracture stress (σF: 25, 100, 250 kPa) were added (15% w/w) to liquid starch-based model soups and semi-solid protein-based model gels. Sensory profiles were quantified by untrained panellists (n = 54) using the Rate-All-That-Apply (RATA) method. Particle size mainly affected the type of sensory descriptors selected by the subjects, whereas fracture stress of particles determined mainly the perceived intensity of selected descriptors. Soups and gels with small particles (0.8 mm) were mainly perceived as gritty, whereas soups and gels with medium-sized particles (2.4 mm) were mainly perceived as beady. Increasing particle size to 4.2 mm caused lumpy and heterogeneous sensations in soups and gels. With variations of particle fracture stress, the perceived intensity of the selected attributes increased or decreased significantly for all particle sizes. Mouthfeel heterogeneity and chewiness increased significantly when increasing the fracture stress from 20 to 100 or 250 kPa. Mechanical contrast did not enhance liking of model soups and gels probably because к-carrageenan particles were perceived as artificial and provided texture contrast without flavour contrast. We conclude that size and fracture stress of dispersed particles embedded in liquid and semi-solid model food matrices affect differently sensory perception with particle size determining type of sensory descriptors selected and particle fracture stress determining intensity of selected sensory attributes.

Poisonous Shrimp Detection System for Litopenaeus Vannamei using k-Nearest Neighbor Method

One of the important seafoods in the food consumption of humans is shrimp. Although shrimp contains proteins that are needed by the human body, sometimes it contains toxins. This is due to environmental factors or catching processes that may use toxins. Therefore, the community should take precautions when consuming shrimp. White shrimp (Litopenaeus vannamei) is one type of shrimp that is preferred because of its delicious taste. The purpose of this research is to develop a computerized system for poisonous white shrimp detection. The category of white shrimps consists of two kinds, i.e., fresh white shrimps that are caught in a natural way (class A), and poisonous white shrimps that are caught by using toxin (class B). The features used are RGB colors (red, green, and blue) and texture (energy, contrast, correlation, and homogeneity). A similarity-based classification is performed by the k-Nearest Neighbor (k-NN) algorithm. The experiment was conducted on a dataset consisting of 90 white shrimp images. The holdout validation method was used to evaluate the system. The original dataset was divided into two parts, whereby 60 images were used as training samples and 30 images were used as testing images. Based on the evaluation results, it can be concluded that the classification accuracy is 73.33%. The benefit of the developed system is to help the community in selecting good and safe white shrimps.

Mechanical properties affect detectability of perceived texture contrast in heterogeneous food gels

This study investigated the influence of mechanical and physicochemical properties of semi-solid model foods on the detection and temporal perception of texture contrast. Gel-based model foods consisting of two layers were used to systematically vary mechanical contrast and physicochemical properties within bi-layer gels. Fracture stress (σF) and strain (εF) were modified by changing the concentration of various gelling agents (agar, к-carrageenan, and gelatine). The physicochemical properties of gels varied with respect to syneresis and melting behaviour depending on the type of gelling agent. The detection limit of perceived texture contrast of bi-layer gels was determined using ranking tests. Subjects ranked gels in order of increasing perceived heterogeneity as a measure of texture contrast. The detection limit of texture contrast varied between brittle and elastic gels and between soft (low σF) and hard (high σF) gels. In soft and brittle agar gels, heterogeneity was perceived already when the difference in fracture stress between layers was small (ΔσF ≥5 kPa). In soft and elastic gels (к-carrageenan, gelatine) and hard gels, heterogeneity was perceived only when the difference in fracture stress between the layers was large (ΔσF ≥12 kPa). The perceived heterogeneity intensity over time was investigated by time-intensity profiling. During mastication, gelatine gels were perceived for a longer period of time with a higher heterogeneity intensity than agar and к-carrageenan gels. We conclude that mainly mechanical properties of gels impact detectability of mechanical contrast as perceived texture contrast (heterogeneity), whereas a combination of mechanical and physicochemical properties influence the dynamic perception of heterogeneity over time.

Carotid artery ultrasound texture, cardiovascular risk factors, and subclinical arterial disease: the Multi-Ethnic Study of Atherosclerosis (MESA).

This pilot study determined if the ultrasound texture feature "contrast" was associated with cardiovascular disease (CVD) risk factors and subclinical arterial disease. We evaluated ultrasound images of the right common carotid artery (CCA) from a convenience sample of 151 participants and examined relationships between contrast, CVD risk factors, carotid intima-media thickness (IMT) and coronary artery calcium (CAC). Grey level difference statistics algorithms were used to evaluate the texture feature "contrast" from carotid ultrasound images. Right CCA IMT measurements were made in triplicate in the distal 1 cm segment of the far wall of the artery and CAC score was measured using the Agatston scoring method. In individual models that included age, sex and race, grey level difference statistics contrast (outcome) was associated independently with age [beta (standard error) = -0.87 (0.38) per year; p = 0.02], C-reactive protein [-2.22 (0.96) per mg dl-1; p = 0.02], high-density lipoprotein cholesterol [0.61 (0.24) per mg dl-1; p = 0.01] and CCA IMT [-0.06 (0.02) microns; p = 0.001]. Other CVD risk factors and CAC were not associated independently with contrast. These findings support the potential use of the ultrasound texture contrast for evaluating arterial injury and CVD risk. Advances in knowledge: This paper contributes to the literature in that it describes how the greyscale texture feature "contrast" is related to CVD risk factors.

Drip irrigation wetting patterns and nitrate distribution: comparison between electrical resistivity (ERI), dye tracer, and 2D soil–water modelling approaches

Despite the widespread use of drip irrigation and fertigation, there is limited research on soil wetting patterns and nutrient distribution from drip emitters in agricultural soils. We compared the use of electrical resistivity imaging (ERI) with dye tracer patterns, measured soil nitrate distribution, and modelled changes in soil moisture and nitrate distribution, in a commercial apple orchard in southern Tasmania. Time-lapse two-dimensional ERI revealed wetting plumes beneath the emitters ranged from nil infiltration, to infiltration beyond 1.0 m depth. Lack of infiltration beneath some emitters was attributed to runoff caused by either water repellence or the surface leaf mulch, whilst infiltration to 1.0 m depth was attributed to preferential flow processes. The uncalibrated ERT was unable to discern the separate contributions from of solute concentration, moisture content and temperature to the change in electrical resistivity. The dye tracer study revealed the majority of the fertigated nitrate was retained in the A1 horizon, whilst the fertigated water infiltrated much deeper into the A2 and B2 horizons. The 2D modelling was not able to replicate the variations in infiltration demonstrated by the ERT, principally due to the lumped nature of the soil parameterisation, and inability of the model to simulate preferential flow. As such, use of modelling tools and texture-based guidelines for design and management of drip emitters is not recommended for the texture contrast soils.

Image Quality Evaluation in Clinical Research: A Case Study on Brain and Cardiac MRI Images in Multi-Center Clinical Trials.

Magnetic resonance imaging (MRI) system images are important components in the development of drugs because it can reveal the underlying pathology in diseases. Unfortunately, the processes of image acquisition, storage, transmission, processing, and analysis can influence image quality with the risk of compromising the reliability of MRI-based data. Therefore, it is necessary to monitor image quality throughout the different stages of the imaging workflow. This report describes a new approach to evaluate the quality of an MRI slice in multi-center clinical trials. The design philosophy assumes that an MRI slice, such as all natural images, possess statistical properties that can describe different levels of contrast degradation. A unique set of pixel configuration is assigned to each possible level of contrast-distorted MRI slice. Invocation of the central limit theorem results in two separate Gaussian distributions. The central limit theorem says that the mean and standard deviation of pixel configuration assigned to each possible level of contrast degradation will follow a normal distribution. The mean of each normal distribution corresponds to the mean and standard deviation of the underlying ideal image. Quality prediction processes for a test image can be summarized into four steps. The first step extracts local contrast feature image from the test image. The second step computes the mean and standard deviation of the feature image. The third step separately standardizes each normal distribution using the mean and standard deviation computed from the feature image. This gives two separate z-scores. The fourth step predicts the lightness contrast quality score and the texture contrast quality score from cumulative distribution function of the appropriate normal distribution. The proposed method was evaluated objectively on brain and cardiac MRI volume data using four different types and levels of degradation. The four types of degradation are Rician noise, circular blur, motion blur, and intensity nonuniformity also known as bias fields. Objective evaluation was validated using a proposed variation of difference of mean opinion scores. Results from performance evaluation show that the proposed method will be suitable to monitor and standardize image quality throughout the different stages of imaging workflow in large clinical trials. MATLAB implementation of the proposed objective quality evaluation method can be downloaded from (https://github.com/ezimic/Image-Quality-Evaluation).

Conservatively treated knee injury is associated with knee cartilage matrix degeneration measured with MRI-based T2 relaxation times: data from the osteoarthritis initiative.

To investigate the association of cartilage degeneration with previous knee injuries not undergoing surgery, determined by morphologic and quantitative 3-T magnetic resonance imaging (MRI). We performed a nested cross-sectional study of right knee MRIs from participants in the Osteoarthritis Initiative (OAI) aged 45-79 with baseline Kellgren-Lawrence score of 0-2. Cases were 142 right knees of patients with self-reported history of injury limiting the ability to walk for at least 2 days. Controls were 426 right knees without history of injury, frequency-matched to cases on age, BMI, gender, KL scores and race (1:3 ratio). Cases and controls were compared using covariate-adjusted linear regression analysis, with the outcomes of region-specific T2 mean, laminar analysis and heterogeneity measured by texture analysis to investigate early cartilage matrix abnormalities and the Whole-Organ Magnetic Resonance Imaging Score (WORMS) to investigate morphologic knee lesions. Compared to control subjects, we found significantly higher mean T2 values in the injury [lateral tibia (28.10ms vs. 29.11ms, p=0.001), medial tibia (29.70ms vs. 30.40ms, p=0.014) and global knee cartilage (32.73ms vs. 33.29ms, p=0.005)]. Injury subjects also had more heterogeneous cartilage as measured by GLCM texture contrast, variance and entropy (p<0.05 in 14 out of 18 texture parameters). WORMS gradings were not significantly different between the two groups (p>0.05). A history of knee injury not treated surgically is associated with higher and more heterogeneous T2 values, but not with morphologic knee abnormalities. Our findings suggest that significant, conservatively treated knee injuries are associated with permanent cartilage matrix abnormalities.

Computer extracted nuclear features from tumor and benign regions of Feulgen and H&amp;E images to help predict recurrence in prostate cancer patients following radical prostatectomy.

e16556 Background: Following radical prostatectomy, around 30% of prostate cancer (PCa) patients experience biochemical recurrence (BCR). H&amp;E highlights nuclear morphology and Feulgen reflects nuclear DNA content, a feature linked to PCa presence and aggressiveness. In this work we sought to explore whether computer extracted measurements of tumor morphology and tumor adjacent benign regions on H&amp;E and Feulgen tissue images could predict BCR. Methods: We used 108 patients (59 BCR and 49 non-recurrence (NR)) and each patient had 242 QH features calculated from both the tumor and benign region of stained TMA core images. Feature selection was performed on a training set (30 BCR, 24 NR) to select the 10 most discriminating tumor and tumor adjacent benign features of each stain. A random forest classifier was trained with features so identified and validated on a test set (29 BCR, 25 NR) to predict BCR. Predictions were displayed using Kaplan-Meier analysis and area under the ROC curve (AUC). Results: The most discriminating feature from the tumor regions of the H&amp;E stain was Fourier descriptors of nuclear shape and from the Feulgen stain was texture intensity while from the benign regions it was invariant moments of nuclear shape and texture contrast energy. Combining the significant features from tumor and tumor adjacent benign regions from H&amp;E and Feulgen resulted in the highest accuracy and a statistically significant difference (p &lt; 0.05) via a log-rank test (Table 1). Gleason score did not show statistically significant differences and had the lowest AUC. Conclusions: Combining nuclear morphology and DNA related features of the tumor and tumor adjacent benign regions enabled accurate prediction of BCR. With additional multi-site validation, the combined H&amp;E + Feulgen classifier could allow better risk stratification and post-surgical patient management. [Table: see text]

Abstract 598: Carotid Artery Ultrasound Texture, Cardiovascular Risk Factors, and Subclinical Arterial Disease: The Multi-Ethnic Study of Atherosclerosis (Mesa)

Background: Ultrasound texture “contrast” can be used to characterize the arterial wall non-invasively. Texture contrast provides information about the distribution and gray level differences of the pixels in the arterial wall and may describe early changes related to arterial injury. We determined if ultrasound texture contrast was associated with cardiovascular disease (CVD) risk factors and subclinical arterial disease. Methods: We evaluated ultrasound images of the distal right common carotid artery from a convenience sample of 151 participants from the first examination of the Multi-Ethnic Study of Atherosclerosis, a population-based cohort of individuals without clinical CVD. Images were digitized, normalized, and standardized to a pixel density of 20/mm. Plaque texture analysis software (LifeQ Medical, Cyprus) used the gray level difference statistics method to determine the contrast of the far wall of the carotid intima-media complex. Multivariable linear regression models (adjusted for age, sex and race/ethnicity) were used to examine relationships between contrast, CVD risk factors (age, BMI, total cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol, triglycerides, hypertension, diabetes mellitus, smoking, glomerular filtration rate, C-reactive protein, interleukin-6, D-dimer, fibrinogen, alcohol consumption, education level, physical activity level, statin use), carotid intima-media thickness (IMT), coronary artery calcium (CAC), and CVD risk score. Results: The 151 participants were mean (standard deviation) 68.1 (9.2) years old (54% female; 31% Hispanic, 28% Black, 10% Chinese, and 31% White). In models that included age, sex, and race, contrast was associated independently with age (beta [standard error] -0.9 [0.4] per year; p=0.02), HDL-C (0.6 [0.2] per mg/dL; p=0.02), C-reactive protein (-2.3 [0.9] per mg/L; p=0.02), and carotid IMT (-1.3 [0.4] microns; p=0.001). Other CVD risk factors and CAC were not associated independently with contrast. Conclusions: Lower contrast, an ultrasound texture feature, is associated with increasing age, lower HDL-C, higher CRP, and higher carotid IMT, supporting its potential use for evaluating arterial injury and CVD risk.

How to design a recto-verso print displaying different images in various everyday-life lighting conditions

This study aims at explaining how to design multi-view prints that can show different images in different illumination conditions. A recent reflectance-transmittance optical model for recto-verso halftone prints is extended in order to fasten the calibration step and is used, according to an inversed approach, to design the recto-verso prints displaying the different images in their respective illumination modes. The good prediction accuracy of the model allows creating special effect prints, such as transformation of a binary image in one mode into a second binary image in the second mode, or the transformation of color image into a grey-level version, or the revelation of a message by texture contrast. Regarding the illumination conditions, simultaneous illumination of both sides of the print is allowed. The difficulty of designing such print comes from the fact that the images that are printed on the two sides of the paper are not the images that are displayed, and that the colors displayable in one mode depend on the colors wanted in the other mode. Since no general color management method for these kinds of prints is available, ad hoc methods are proposed for the different effects considered.

Adaptive Image Compressive Sensing Using Texture Contrast

The traditional image Compressive Sensing (CS) conducts block-wise sampling with the same sampling rate. However, some blocking artifacts often occur due to the varying block sparsity, leading to a low rate-distortion performance. To suppress these blocking artifacts, we propose to adaptively sample each block according to texture features in this paper. With the maximum gradient in 8-connected region of each pixel, we measure the texture variation of each pixel and then compute the texture contrast of each block. According to the distribution of texture contrast, we adaptively set the sampling rate of each block and finally build an image reconstruction model using these block texture contrasts. Experimental results show that our adaptive sampling scheme improves the rate-distortion performance of image CS compared with the existing adaptive schemes and the reconstructed images by our method achieve better visual quality.

Virtual palaeontology: the effects of mineral composition and texture of fossil shell and hosting rock on the quality of X-ray microtomography (XMT) outcomes using Palaeozoic brachiopods

X-ray microtomography (XMT) has become a popular tool for detailed investigations of a diverse range of fossils. However, XMT has not always guaranteed a satisfactory result, as the resolution of XMT images critically depends on the contrast between the fossil and its hosting rock. In this paper, XMT was applied to 11 Palaeozoic brachiopod specimens selected from a range of sedimentary rocks in order to investigate the extent of effects of mineral composition and texture in the rock and fossil shell on the quality of XMT outcomes. Our study shows that sufficient contrast in mineral composition and texture between the brachiopod shell and its infilling material is required to reproduce high-quality XMT results. Specifically, brachiopod specimens with their original calcium carbonate shell, infilled mainly with quartz grains, appear to produce the best XMT results characterized by sharply defined shell internal structures. We also found that diagenesis is significant in determining the XMT quality. Diagenetic processes including silicification and recrystallization in the brachiopod shell and/or the infilling material generally tends to diminish the resolution of the XMT results, although this impact is considerably complicated by the degree and aspect of diagenesis. Another factor of minor significance concerns the presence of bioclasts scattered in the hosting sediment that potentially could be confused with genuine shell internal structures.