Image Size Reduction Research Articles

Effect of the image resolution on the statistical descriptors of heterogeneous media

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Complete description of the optical path difference of a novel spectral zooming imaging spectrometer

A complete description of the optical path difference of a novel spectral zooming imaging spectrometer (SZIS) is presented. SZIS is designed based on two identical Wollaston prisms with an adjustable air gap. Thus, interferogram with arbitrary spectral resolution and great reduction of spectral image size can be conveniently formed to adapt to different application requirements. Ray tracing modeling in arbitrary incidence with a quasi-parallel-plate approximation scheme is proposed to analyze the optical path difference of SZIS. In order to know the characteristics of the apparatus, exact calculations of the corresponding spectral resolution and field of view are both derived and analyzed in detail. We also present a comparison of calculation and experiment to prove the validity of the theory.

Porting a PCA-based hyperspectral image dimensionality reduction algorithm for brain cancer detection on a manycore architecture

This paper presents a study of the parallelism of a Principal Component Analysis (PCA) algorithm and its adaptation to a manycore MPPA (Massively Parallel Processor Array) architecture, which gathers 256 cores distributed among 16 clusters. This study focuses on porting hyperspectral image processing into manycore platforms by optimizing their processing to fulfill real-time constraints, fixed by the image capture rate of the hyperspectral sensor. Real-time is a challenging objective for hyperspectral image processing, as hyperspectral images consist of extremely large volumes of data and this problem is often solved by reducing image size before starting the processing itself. To tackle the challenge, this paper proposes an analysis of the intrinsic parallelism of the different stages of the PCA algorithm with the objective of exploiting the parallelization possibilities offered by an MPPA manycore architecture. Furthermore, the impact on internal communication when increasing the level of parallelism is also analyzed. Experimenting with medical images obtained from two different surgical use cases, an average speedup of 20 is achieved. Internal communications are shown to rapidly become the bottleneck that reduces the achievable speedup offered by the PCA parallelization. As a result of this study, PCA processing time is reduced to less than 6 s, a time compatible with the targeted brain surgery application requiring 1 frame-per-minute.

CWS Compression: Cascading of Wavelet difference Reduction and Singular Value Decomposition

People are sharing, transmitting and storing millions of images every day. To store images it may require huge data storage. The compression of images reduces the storage required to store images, also permits the faster transmission. Several works have been carried out in designing compression techniques that reduce image size with higher image quality. True color images take largest part in web pages, hence it is important to make control over image size and their quality to deliver fastest loading. This paper presents a new image compression technique CWS by cascading wavelet difference reduction (WDR) and singular value decomposition(SVD). In the proposed method, an input image is first compressed using WDR and then compressed using SVD. These two techniques are cascaded to boost the performance of WDR. The results are showing that the proposed compression is superior over the aforementioned compression techniques.

Design and Implementation of Iris Pattern Recognition Using Wireless Network System

The goal of this paper is to propose a fast and accurate iris pattern recognition system by using wireless network system. This paper consists of three parts: the first part includes two methods of the iris pattern recognition system: Libor Masek and genetic algorithms, the second part includes the compression-decompression process of iris image using Principal Component Analysis (PCA) as a data reduction method, in order to reduce image size, and the third part talks about wireless network. In this work, an iris image is transferred across wireless network which contains two independent-parallel lines connected to the central Personal Computer (PC) in order to be recognized at the end of each line, then the results of recognition are sent back to the central PC. The proposed genetic algorithm, which is used in this paper is more accurate than Masek algorithm and has low computational time and complexity, which makes this method better than Masek method in recognizing iris patterns.

Sub-10 nm nanopantography

Nanopantography, a massively parallel nanopatterning method over large areas, was previously shown to be capable of printing 10 nm features in silicon, using an array of 1000 nm-diameter electrostatic lenses, fabricated on the substrate, to focus beamlets of a broad area ion beam on selected regions of the substrate. In the present study, using lens dimensional scaling optimized by computer simulation, and reduction in the ion beam image size and energy dispersion, the resolution of nanopantography was dramatically improved, allowing features as small as 3 nm to be etched into Si.

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

Image Compression using CDF5/3 Wavelet Transform Coupled with Bit Plane Algorithm

The near future of image processing techniques state the compatibility issues of applied algorithms with storage techniques and data transmission across noisy environment. Image compression is a vital element that is employed due to its characteristics of image size reduction without considerable data loss. This paper employs an SAR image compression technique based on CDF 5/3 in unison with bit plane algorithm. The CDF 5/3 encodes the real images converted by fast Fourier transform (FFT). The performance analysis is observed by changing in BPP (Bit per pixel) for a given image and based on varying BPP peak signal-to-noise ratio (PSNR) and (Mean square Error) MSE. General Terms Image processing, SAR image, wavelet transform, Directional lifting wavelet transform.

An Object-Based Image Reducing Approach

Common methods for reducing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image reducing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

ADAPTIVE EDGE DETECTION USING ADJUSTED ANT COLONY OPTIMIZATION

Abstract. Edges contain important information in image and edge detection can be considered a low level process in image processing. Among different methods developed for this purpose traditional methods are simple and rather efficient. In Swarm Intelligent methods developed in last decade, ACO is more capable in this process. This paper uses traditional edge detection operators such as Sobel and Canny as input to ACO and turns overall process adaptive to application. Magnitude matrix or edge image can be used for initial pheromone and ant distribution. Image size reduction is proposed as an efficient smoothing method. A few parameters such as area and diameter of travelled path by ants are converted into rules in pheromone update process. All rules are normalized and final value is acquired by averaging.

PPI-SVM-Iterative FLDA Approach to Unsupervised Multispectral Image Classification

This paper presents a new approach to unsupervised classification for multispectral imagery. It first implements the pixel purity index (PPI) which is commonly used in hyperspectral imaging for endmember extraction to find seed samples without prior knowledge, then uses the PPI-found samples as support vectors for a kernel-based support vector machine (SVM) to generate a set of initial training samples. In order to mitigate randomness caused by PPI and sensitivity of support vectors used by SVM it further develops an iterative Fisher's linear discriminate analysis (IFLDA) that performs FLDA classification iteratively to produce a final set of training samples that will be used to perform a follow-up supervised classification. However, when the image is very large, which is usually the case in multispectral imagery, the computational complexity will be very high for PPI to process the entire image. To resolve this issue a Gaussian pyramid image processing is introduced to reduce image size. The experimental results show the proposed approach has great promise in unsupervised multispectral classification.

Abstract WMP118: Involvement of MMP-9 in Inflammation-induced White Matter Injury in a Novel Rat Model of Vascular Cognitive Impairment

Objective: We have recently developed a rat model of white matter (WM) injury in stroke-prone spontaneously hypertensive rats (SHR-SP), which shows chronic oligodendrocyte death, blood-brain barrier (BBB) disruption, and cognitive impairment. In this study, we investigated the mechanisms of white matter damage secondary to chronic hypertensive disease. Methods: At 12 weeks of age, we subjected SHR-SP to permanent unilateral carotid artery occlusion (UCAO) followed by the Japanese permissive diet (JPD) and 1 % NaCl in drinking water. One group of UCAO/JPD rats received minocycline (50 mg/kg in DMSO, i.p. every other day for 9 weeks) and another had only UCAO/JPD with DMSO. WM lesions were characterized histologically, biochemically, and by MRI; cognitive impairment was tested by Morris water maze. Results: One to 3 weeks after UCAO/JPD, we found an increase in hypoxia inducible factor-1α (HIF-1α) in astrocytes, a fall in pyrol hydroxylase-2 (PHD-2), and an increase in matrix metalloproteinase-9 (MMP-9) expression. At week 1, there was infiltration of T-cells and MMP-9 co-localized with endothelial cells and neutrophils. By 3 weeks, we observed IgG leakage, indicating disruption of the BBB, with scattered hemorrhages. Long term treatment with minocycline prevented cognitive impairment along with reduction in T2-weighted image size, apparent diffusion coefficients, and fractional anisotropy compared to the vehicle-treated group. Relative cerebral blood flow was unaffected by minocycline treatment. Conclusion: Our results suggest that hypoxic hypoperfusion of the deep WM, which occurs secondary to hypertensive damage to blood vessels, initiates expression of MMP-9 and migration of T-cells, disrupting the BBB and damaging WM. The anti-inflammatory agent, minocycline, significantly protected the deep WM from injury.

Ring Falling into a Chain: No Magic — Just Physics

Magic tricks are very popular, and they can and should be used in teaching when the underlying principle is easily explained by physics. Such tricks often fall in the realm of hands-on experiments, which are considered to be potentially very effective in raising interest and motivating students.1 Unfortunately, many hands-on experiments are easy to do, but more difficult to explain. One of the reasons is that they often happen so fast that the underlying principle can only be guessed. Also, a magic trick can be disguised so that an observer cannot solve the puzzle with the naked eye. Quite often even regular camcorders do not provide the necessary time resolution. Fortunately, however, huge advances in microsystem technologies have recently led to the development of commercially available high-speed cameras that are relatively inexpensive. The low end of the price range is now at or below $300.2 Some models of the Casio Exilim series provide up to 1200 frames per second for reduced image size. The technology of such cameras has been extensively summarized elsewhere,3 and many nice examples of experiments recorded with high-speed imaging are under way.4 Here we present one example of a physics “magic trick” that is extremely easy to perform while giving stunning results. High-speed images (snapshots and movies) can nicely reveal the physics behind the trick.

Detection of proximal caries with high-resolution and standard resolution digital radiographic systems

The aim of this study was to: (1) compare the diagnostic accuracy of the high-resolution and standard resolution settings of four digital imaging systems for caries diagnosis and (2) compare the effect on the diagnostic accuracy of reducing the high-resolution image sizes to the standard resolution dimensions, and vice versa. 90 extracted human premolars were mounted in groups of 5 in plaster blocks, containing 4 test teeth and 1 non-test tooth. Two blocks at a time were placed in a jig to simulate a bitewing radiograph. Radiographs were taken using four digital systems (Planmeca Dixi 2; Gendex Visualix HDI; Dürr Vistascan; Digora Optime), each at two resolution settings. Next, the teeth were sectioned and a total of 65 surfaces were incorporated in the study. Additionally, the bicubic interpolation method was applied to reduce the high-resolution original images and to enlarge the standard resolution images. The original, reduced and enlarged images were randomly shown to five observers in two random sessions. The observers were asked to assess caries depth on a 4-point scale. The observers' scores were compared with the results from a histological examination. Data were analysed using the statistical theory for multivariate discrete data. Cohen's kappa was used to determine the agreement with the gold standard. None of the comparisons between the spatial resolution settings, or the comparisons between increased or reduced image size and the original image sizes, showed significant differences in the probability of caries detection (chi2=26.59, df=26, P approximately 0.50). The four digital systems used in this study differ significantly in the probability of caries detection (chi2=41.55, df=24, P<0.02). Compared with the gold standard, the Gendex Visualix HDI CCD sensor has the highest measure of agreement (kappa=0.31). Caries diagnosis does not improve when using high-resolution settings compared with the standard settings. The use of bicubic convolution interpolation for zooming has no detectable effect on caries diagnosis and therefore is recommended to use when enlarging or reducing radiographs. The probability of caries detection, however, was different for the sensor systems of the different manufacturers.

NEURONAVIGATIONAL ENDOSCOPIC ENDONASAL SELLAR AND PARASELLAR SURGERY USING A 2-MM–DIAMETER LENS RIGID–ROD ENDOSCOPE

Most of the endoscopes used for endonasal transsphenoidal surgery use 4-mm diameter lenses. The applicability of a newly developed neuroendoscope with a lens diameter of only 2 mm was tested in endonasal transsphenoidal pituitary surgery. The newly developed rigid-rod neuroendoscope with a 2-mm lens and an endoscope with a 4-mm lens were coupled with a navigation system and used for this comparative study. Comparison between the views obtained with these two devices was performed in a model and in formalin-fixed cadaver heads. A pure endonasal approach was used to reach and explore the sellar and parasellar regions. The navigation system was used to locate the same position in both lenses for image comparison. The sellar and parasellar regions could be reached and explored using the new endoscope with the 2-mm lens and an oval-shaped irrigation and suction channel. The visual field appeared to be reduced compared with that of the 4-mm lens. However, this reduction was compensated by greater mobility and easier introduction and maneuvering of the instruments at the sellar level. Reduced image size and brightness were also found using the 2-mm lens compared with the 4-mm lens. These differences could be overcome by increasing the amount of light and enlarging the image but with subsequent reduction in image resolution. The small diameter of this neuroendoscope resulted in good maneuverability and maintained a fine quality of vision. Children and patients with small nostrils are good candidates for the use of such a device.

Interest in healthy living outweighs presumed cultural norms for obesity for Ghanaian women

BackgroundCultural norms indicate that obesity reflects increased wealth and prosperity. Yet obesity is linked to serious medical illnesses. The purpose of this study was to determine if Ghanaian women would change their body image if it meant a healthier life.MethodsA questionnaire was administered to 305 Ghanaian women waiting for clinic appointments at Korle Bu Teaching Hospital, Accra Ghana. This survey included questions on current health, selection of figural stimuli, decision making on health and social determinants and 5 questions on self-perception of health from SF-36. Anthropometric measures were taken and body mass index calculated. Women were also provided with health related information at the conclusion of the interview.ResultsThe majority of all women surveyed would reduce their current body image if it meant that they would have an overall healthier life and reduce the risks of obesity-linked illnesses and complications. Currently obese women were significantly more likely than non-obese women to reduce their body image to reduce the risk of hypertension (OR 2.03 [1.64 – 2.51],<0.001); cardiovascular accident (OR 1.96 [1.61 – 2.38],<0.001); diabetes (OR 2.00 [1.63 – 2.44],<0.001); myocardial infarction (OR 2.27 [1.80 – 2.86],<0.001); if requested by a spouse(OR 2.64 [1.98 – 3.52],<0.001); and to improve overall health (OR 1.95 [1.60 – 2.37], <0.001). There was no association with current body image and responses to SF-36. The decision to select a new body image was not influenced by education, income, marital status or parity. Age 50 years old and less was significantly associated with the body image size reduction to reduce the risk of hypertension, diabetes, and a cardiovascular accident.ConclusionThe Ghanaian women interviewed in this study are interested in living a healthy life and are willing to reduce their body size to reduce the risk of obesity-linked illnesses. The target group for any interventional studies and measures to reduce obesity appears to be women age 50 and younger.

High Quality Raster Image Resizing Using Linear Weighted Manipulation

Due to the versatile customer applications and especially for large size industrial printing needs, the conflict comes between the image enlargement and high resolution quality. The image resizing process introduces specific pixels to the original image, or leaves out specific pixels from the original image. In order to maintain image quality and non-distortion, the value of such pixels and their positions were carefully deliberated. Prior researches such as DCT-based [2], wavelets, pixel replication linear interpolation [1] [3] those were limited by bandwidth and storage spaces, therefore a high efficiency resizing method is proposed in this paper. We introduce a new simple and high quality image-resizing algorithm that using linear weighted method for enlarging and drawing out particular pixels for reducing image size. The enlarging is first procedure and following with reducing procedure, where the image boundaries between those procedures needed to be carefully identification by linear weighted to avoid resolution loss. The simulation suggested the image can be enlarged up to four times and reduced down to quarter of original image at no resolution deterioration, and save the storage space need of fifty percent. Besides, the separation procedure is independent on enlarging procedure that can be operated if the image only needs to be reduced, same performance as mentioned before. This algorithm had been implemented by hardware and it will easily operate in software function in near future.

Telemedicine in Ophthalmology: A Useful Tool in Store-and-Forward Counselling?

Side by side with the progress in computers and imaging, telemedicine has already been used successfully in a large number of specialties of medicine. But high-quality images are not always suitable for transfer via modem because of their file size. The present experimental study was conducted to determine the effects of image compression by the JPEG algorithm on image quality and on the reliability of diagnosis after compression. Digital photographs of the retina were taken and the JPEG compressed images assessed by an experienced ophthalmologist. The present study showed a high reliability of diagnosis and a good agreement between the observations taken at the patient and at the computer. For this reason, JPEG image compression algorithm is suitable for reducing image size for producing high-quality images manageable for transmitting via modem in a store-and-forward teleophthalmological system.

X-ray diffraction topography using a diffractometer with a bendable monochromator at a synchrotron radiation source.

The different properties of laboratory- and synchrotron-based double-crystal setups for X-ray topographic applications are discussed as a basis for the realization of a versatile instrument allowing the investigation of all kinds of crystals with high strain sensitivity and without any reduction in image size. It appears that the use of a bendable highly perfect monochromator (silicon) achieves this goal, through the local adaptation of Bragg angles, to compensate either dispersion or a bending of the sample.

Influence of CT image size and format on accuracy of lung nodule detection.

To evaluate the effect of reducing image size on observers' ability to detect lung nodules on computed tomographic (CT) scans. Stimuli were 80 single sections from 13 normal chest CT studies. On half of the images, 3-5-mm-diameter nodules were superimposed electronically at random locations. Four observers viewed images in six formats and sizes that ranged from 6 on 1 (133 x 133 mm) to 80 on 1 (40 x 40 mm). The images were viewed at a fixed distance of 55 cm and at an unrestricted, variable distance. With the fixed viewing distance, nodule detection decreased with smaller image sizes. The area under the receiver operating characteristic curve (Az) decreased from 0.857 for the 6-on-1 format to 0.671 for the 80-on-1 format (P = .0001). With a variable viewing distance, Az decreased from 0.884 to 0.834 across all formats (difference not statistically significant). However, there was a significant drop in performance with the smallest images (P < .05). Overall, Az for the fixed and variable viewing distances was significantly different (P < .001). Reducing image size leads to decreased lung nodule detection on CT scans viewed at a fixed distance; however, the observer can compensate for the smaller image by adjusting the viewing distance.