Image Luminance Research Articles

Self-tunable transformation function for enhancement of high contrast color images

A new image enhancement technique based on a self-tunable transformation function to improve the visual quality of images captured with low dynamic range devices in extreme lighting conditions is presented. This technique consists of four processes: histogram adjustment, dynamic range compression, contrast enhancement, and nonlinear color restoration. Histogram adjustment on each spectral band is performed to minimize the effect of illumination. Dynamic range compression is accomplished by a newly designed inverse sine nonlinear function that provides various nonlinear curvatures with an image dependent parameter. A nonlinear curve generated by this parameter is used to modify the intensity of each pixel in the luminance image. A nonlinear color restoration process based on the chromatic information and luminance of the original image is employed. The effectiveness of this technique is evaluated on various natural images and aerial images, and compared with other state-of the art techniques. A quantitative evaluation is performed by estimating the number of Harris corners and speeded up robust features on wide area motion imagery data. The application of the proposed algorithm on face detection is also demonstrated. The evaluation results demonstrate that the proposed method holds significant benefits for surveillance and security applications and also as a preprocessing technique for object detection and tracking applications.

Research on the Technology of Partial Masked Target Recognition

The result of target recognition is always influenced by the clutter background, low contrast and deficiency luminance of image. Besides the factors mentioned above, detection and recognition of partial masked target has the character of fragmented target, which leads to another problem. All the harmful factors cause that target recognition can not be realized by hybrid optoelectronic joint transform correlator (HOJTC) due to the weak correlation peaks, even no peaks appear. In this paper, input image of HOJTC is processed by the method of adaptive threshold, and power spectrum is processed by wavelet transform (WT) as well. The combination effectively controls the disturbance of noise and enhances the energy of diffractive light of target. Experiment of HOJTC shows that the method can enhance the contrast of correlation peaks of partial masked target and improve the detection and recognition capacity of HOJTC. As an example, the experiment results of fragmented airplane target before and after processing are shown in the paper, which demonstrate the effectiveness of the method.

Spatial Objects Shaping with High-Pressure Abrasive Water Jet Controlled By Virtual Image Luminance

Spatial Objects Shaping with High-Pressure Abrasive Water Jet Controlled By Virtual Image Luminance

Generating stereoscopic HDR images using HDR-LDR image pairs

A number of novel imaging technologies have been gaining popularity over the past few years. Foremost among these are stereoscopy and high dynamic range (HDR) Imaging. While a large body of research has looked into each of these imaging technologies independently, very little work has attempted to combine them. This is mostly due to the current limitations in capture and display. In this article, we mitigate problems of capturing Stereoscopic HDR (SHDR) that would potentially require two HDR cameras, by capturing an HDR and LDR pair and using it to generate 3D stereoscopic HDR content. We ran a detailed user study to compare four different methods of generating SHDR content. The methods investigated were the following: two based on expanding the luminance of the LDR image, and two utilizing stereo correspondence methods, which were adapted for our purposes. Results demonstrate that one of the stereo correspondence methods may be considered perceptually indistinguishable from the ground truth (image pair captured using two HDR cameras), while the other methods are all significantly distinct from the ground truth.

1C1-1 単眼シースルーヘッドマウントディスプレイの映像輝度とユーザの眼球運動特性の関係

1C1-1 単眼シースルーヘッドマウントディスプレイの映像輝度とユーザの眼球運動特性の関係

Perception Enhancement through Additional Illumination

This paper presents a new strategy to counter camouflage by capturing (one more) additional images of same scene. The strategy is based on a technique we call 'two-light photometric stereo', which can remove disruptive reflectance from luminance images to generate synthetically shaded images related only to surface shape information. It becomes easier to perceive concealed information from virtually shaded images free from the effects of a confusing reflectance texture. Various rendered images, corresponding to different synthetic illumination configurations are generated to offer an improved visualization, countering the effects of camouflage. Experiments results are presented using scenes possessing different conventionally 'difficult' back and foreground camouflage. The results verify that the proposed low-cost and robust technique may be used for perception research, security and military applications. Future work will extend the method to more challenging objects in outdoor environments.

Spatio-spectral image statistics and their use in computer vision

There are many computational models for the spatial statistics of grayscale (luminance) images, and in computer vision we rely heavily on these for denoising, deblurring, distinguishing shading from material boundaries, and so on. There are also models for the statistics of spectral point samples, and these are useful for tasks like computational color constancy. What we know less about is whether there are significant correlations between the spatial and spectral dimensions of natural images and, if there are, whether these correlations are useful for vision. I'll describe some attempts at answering these questions, including our collection and analysis of a database of hyperspectral real-world images, and our development of computer vision techniques that leverage spatio-spectral image models. Meeting abstract presented at OSA Fall Vision 2012

Contrast enhancement and noise elimination using singular value decomposition for stereo imaging

A new stereoscopic satellite image enhancement method based on singular value decomposition (SVD) is presented. The proposed stereoscopic image enhancement technique consists of four steps; SVD based on image analysis, image enhancement, noise reduction, and tone consistency. The goal of this work is to enhance low-contrast stereo satellite images with noise elimination, and obtain identical luminance levels from slightly different luminance in stereo images. Experimental results show the proposed method improves contrast performance while maintaining the luminance continuity. It also exhibits less noise than conventional methods.

Viewpoint Selection Using Hybrid Simplex Search and Particle Swarm Optimization for Volume Rendering

In this paper we proposed a novel method of viewpoint selection using the hybrid Nelder-Mead (NM) simplex search and particle swarm optimization (PSO) to improve the efficiency and the intelligent level of volume rendering. This method constructed the viewpoint quality evaluation function in the form of entropy by utilizing the luminance and structure features of the two-dimensional projective image of volume data. During the process of volume rendering, the hybrid NM- PSO algorithm intended to locate the globally optimal viewpoint or a set of the optimized viewpoints automatically and intelligently. Experimental results have shown that this method avoids redundant interactions and evidently improves the efficiency of volume rendering. The optimized viewpoints can focus on the important structural features or the region of interest in volume data and exhibit definite correlation with the perception character of human visual system. Compared with the methods based on PSO or NM simplex search, our method has the better performance of convergence rate, convergence accuracy and robustness.

A robust blind color image watermarking in quaternion Fourier transform domain

Most of the existing color image watermarking schemes were designed to mark the image luminance component only, which have some disadvantages: (i) they are sensitive to color attacks because of ignoring the correlation between different color channels, (ii) they are always not robust to geometric distortions for neglecting the watermark desynchronization. It is a challenging work to design a robust color image watermarking scheme. Based on quaternion Fourier transform and least squares support vector machine (LS-SVM), we propose a robust blind color image watermarking in quaternion Fourier transform domain, which has good visual quality. Firstly, the original color image is divided into color image blocks. Then, the fast quaternion Fourier transform is performed on the color image block. Finally, the digital watermark is embedded into original color image by adaptively modulating the real quaternion Fourier transform coefficients of color image block. For watermark decoding, the LS-SVM correction with pseudo-Zernike moments is utilized. Experimental results show that the proposed color image watermarking is not only robust against common image processing operations such as filtering, JPEG compression, histogram equalization, and image blurring, but also robust against the geometrical distortions.

Three-Dimensional Natural Scene Statistics: Dependencies between Luminance and Range Contrasts

Computing relative or absolute range (egocentric distance) is difficult because, of course, neither is specified in any direct way by the 2D retinal image. If, however, there was a relationship between range and luminance or color, perhaps it could be exploited to yield fast, initial estimates of range from the retinal image per se. We studied the statistical dependence between range (and disparity) contrast and luminance contrast across random point-pairs in natural scenes, and found that changes in range and luminance are highly dependent. We collected high resolution range maps of natural scenes co-registered with luminance (RGB) images using a Riegl terrestrial scanner, co-mounted camera, and in-house software. Various alternative preprocessing stages were used to simulate the early stages of visual processing (e.g. foveation). Our basic approach was to randomly sample pairs of points in the scenes to determine if the change in range or luminance or both exceeded some criterion. We then 1) compared the conditional density of range edges given luminance edges to the (unconditioned) density of range edges and 2) compared the joint distribution of range and luminance contrast to the product of their marginal distributions. We found a robust statistical dependence between range and luminance. Additionally, we computed difference surface maps (between the joint distributions and product-of-marginals predicted by independence). These difference surfaces reveal which regions of luminance and range change exhibit the strongest statistical dependencies. The statistical dependence between luminance and range allows the construction of models where one can assign a probability of occurrence of a range edge given a luminance edge at a particular point in a scene. In principle, such a mechanism could also be used by biological visual system to serve as priors when reconstructing the 3D environment from 2D image data. Meeting abstract presented at VSS 2012

A Fast Dynamic Range Compression With Local Contrast Preservation Algorithm and Its Application to Real-Time Video Enhancement

This study addresses low dynamic range (LDR) image/video enhancement for digital video cameras. A new fast dynamic range compression format with a local-contrast-preservation (FDRCLCP) algorithm resolves this problem efficiently. The proposed FDRCLCP algorithm can combine with any continuously differentiable intensity transfer function to achieve LDR image enhancement. In combination with the FDRCLCP algorithm, a new intensity-transfer function is proposed, adaptively accomplishing dynamic range compression and edge-contrast enhancement depending on the local mean value of the input luminance image. The proposed method also extends to a linear color remapping approach, not only preserving the original image's color information, but also controlling color saturation of the resulting image. Moreover, a look-up-table (LUT) acceleration approach improves the processing speed of the proposed FDRCLCP algorithm in processing video signals, allowing real-time video enhancement processing. Experimental results show that the proposed method not only provides good visual representation in both quantitative and visual comparisons, but also achieves real-time performance for video processing.

에지를 이용한 문서영상의 기울기 보정

본 논문에서 선명 화질은 물론 저화질 문서영상에서 에지를 이용해 문서영상의 기울기를 검출하고, 보정하는 알고리즘을 제안한다. 제안된 알고리즘은 영상 복잡도를 이용해 문자영역을 선택하여 에지를 검출하고, 이들을 다양한 방향으로 투영하여 투영 히스토그램들을 생성한다. 그리고 히스토그램들에서 에지 집중도를 평가하여 문서영상의 기울기를 검출하고 기울어진 문서 영상을 보정한다. 고속 기울기 검출을 위해 부표본화와 3단 coarse-to-fine 탐색 알고리즘을 사용한다. 선명 화질과 저화질 영상의 기울기 검출에서 제안된 알고리즘의 최대 검출 오차와 평균오차가 기존 유사 알고리즘의 50% 정도이고, 기울기 검출 시간은 25%정도로 감소된다. 모바일기기로 취득된 밝기 불균일 영상에서는 기존 알고리즘은 적절한 2진 영상을 얻을 수 없어 기울기 검출이 어려우나 제안된 알고리즘의 평균 검출 오차 0.1o 이하로 기울기를 검출한다. This paper proposes an algorithm detecting the skew of the degraded as well as the clear document images using edge and correcting it. The proposed algorithm detects edges in a character region selected by image complexity and generates projection histograms by projecting them to various directions. And then it detects the document skew by estimating the edge concentrations in the histograms and corrects the skewed document image. For the fast skew detection, the proposed algorithm uses downsampling and 3 step coarse-to-fine searching. In the skew detection of the clear and the degraded images, the maximum and the average detection errors in the proposed algorithm are about 50% of one in a conventional similar algorithm and the processing time is reduced to about 25%. In the non-uniform luminance images acquired by a mobile device, the conventional algorithm can't detect skews since it can't get valid binary images, while the proposed algorithm detect them with the average detection error of 0.1o or under.

Face detection of ubiquitous surveillance images for biometric security from an image enhancement perspective

Security methods based on biometrics have been gaining importance increasingly in the last few years due to recent advances in biometrics technology and its reliability and efficiency in real world applications. Also, several major security disasters that occurred in the last decade have given a new momentum to this research area. The successful development of biometric security applications cannot only minimise such threats but may also help in preventing them from happening on a global scale. Biometric security methods take into account humans’ unique physical or behavioural traits that help to identify them based on their intrinsic characteristics. However, there are a number of issues related to biometric security, in particular with regard to the poor visibility of the images produced by surveillance cameras that need to be addressed. In this paper, we address this issue by proposing an integrated image enhancement approach for face detection. The proposed approach is based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It can adjust the colour cast and maintain the luminance of the whole image at the same level. We evaluate the performance of the proposed approach by applying three face detection methods (skin colour based face detection, feature based face detection and image based face detection) to surveillance images before and after enhancement using the proposed approach. The results show a significant improvement in face detection when the proposed approach was applied.

Noise reduction and adaptive contrast enhancement for local tone mapping

In this paper, we propose a noise reduction method and an adaptive contrast enhancement for local tone mapping (TM). The proposed local TM algorithm compresses the luminance of high dynamic range (HDR) image and decomposes the compressed luminance of HDR image into multi-scale subbands using the discrete wavelet transform. For noise reduction, the decomposed images are filtered using a bilateral filter and soft-thresholding. And then, the dynamic ranges of the filtered subbands are enhanced by considering local contrast using the modified luminance compression function. Finally, the color of the tone-mapped image is reproduced using an adaptive saturation control parameter. We generate the tone-mapped image using the proposed local TM. Computer simulation with noisy HDR images shows the effectiveness of the proposed local TM algorithm in terms of visual quality as well as the local contrast. It can be used in various displays with noise reduction and contrast enhancement.

Visual search performance of patients with vision impairment: effect of JPEG image enhancement

To measure natural image search performance in patients with central vision impairment. To evaluate the performance effect for a JPEG based image enhancement technique using the visual search task. One hundred and fifty JPEG images were presented on a touch screen monitor in either an enhanced or original version to 19 patients (visual acuity 0.4-1.2 logMAR, 6/15 to 6/90, 20/50 to 20/300) and seven normally sighted controls (visual acuity -0.12 to 0.1 logMAR, 6/4.5 to 6/7.5, 20/15 to 20/25). Each image fell into one of three categories: faces, indoors, and collections. The enhancement was realized by moderately boosting a mid-range spatial frequency band in the discrete cosine transform (DCT) coefficients of the image luminance component. Participants pointed to an object in a picture that matched a given target displayed at the upper-left corner of the monitor. Search performance was quantified by the percentage of correct responses, the median search time of correct responses, and an 'integrated performance' measure - the area under the curve of cumulative correct response rate over search time. Patients were able to perform the search tasks but their performance was substantially worse than the controls. Search performances for the three image categories were significantly different (p <= 0.001) for all the participants, with searching for faces being the most difficult. When search time and correct response were analyzed separately, the effect of enhancement led to increase in one measure but decrease in another for many patients. Using the integrated performance, it was found that search performance declined with decrease in acuity (p = 0.005). An improvement with enhancement was found mainly for the patients whose acuity ranged from 0.4 to 0.8 logMAR (6/15 to 6/38, 20/50 to 20/125). Enhancement conferred a small but significant improvement in integrated performance for indoor and collection images (p = 0.025) in the patients. Search performance for natural images can be measured in patients with impaired vision to evaluate the effect of image enhancement. Patients with moderate vision loss might benefit from the moderate level of enhancement used here.

Vector Disparity Sensor with Vergence Control for Active Vision Systems

This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.

Animal detection and identification in natural scenes: Image statistics and emotional valence

Humans process natural scenes rapidly and accurately. Low-level image features and emotional valence affect such processing but have mostly been studied in isolation. At which processing stage these factors operate and how they interact has remained largely unaddressed. Here, we briefly presented natural images and asked observers to report the presence or absence of an animal (detection), species of the detected animal (identification), and their confidence. In a second experiment, the same observers rated images with respect to their emotional affect and estimated their anxiety when imagining a real-life encounter with the depicted animal. We found that detection and identification improved with increasing image luminance, background contrast, animal saturation, and luminance plus color contrast between target and background. Surprisingly, animals associated with lower anxiety were detected faster and identified with higher confidence, and emotional affect was a better predictor of performance than anxiety. Pupil size correlated with detection, identification, and emotional valence judgments at different time points after image presentation. Remarkably, images of threatening animals induced smaller pupil sizes, and observers with higher mean anxiety ratings had smaller pupils on average. In sum, rapid visual processing depends on contrasts between target and background features rather than overall visual context, is negatively affected by anxiety, and finds its processing stages differentially reflected in the pupillary response.

An Improved Method for Generating Colored Pencil Drawing

In this paper, we put forward an improved non-photorealistic rendering method for generating a colored pencil drawing from digital image. First, to make sure the result can retain the original color information, we use the original pixel value instead of the black dot which generated by the traditional white-noise generating method. Second, we added a ratio for the Kirsch operator to be suitable for different images with different details. Third, we present a new approach which extruded form the luminance of the original image to determine the stroke orientation. Based on our methods, the quality of traditional pencil illustration can be guaranteed to a certain extent, and an effective and convenient tool is provided to generate the same drawings in style with artists and illustrations even for the users that have not been trained professionally.

Colour image watermarking for tamper proofing and pattern-based recovery

The rapid development of the internet allows digital media being easily delivered, copied and even tampered. The watermarking issue has thus focused mainly on the medium of authentication. In this study, an efficient self-embedding watermarking scheme for colour image authentication is proposed. The scheme is designed to achieve tamper proofing and high-quality recovery. The scheme is efficient because the validity of image blocks is simply proofed by using a dual-option parity-check method and morphological operations. The former is used to generate authentication information for obtaining better results of tamper proofing and the latter is used to further improve the neighbouring connectivity of the proofing results. To achieve high-quality recovery of the tampered image, the feature information of the host colour image and its corresponding block-edge-pattern information are properly organised to embed into three colour components of the host colour image. Meanwhile, the embedding information is appropriately distributed over luminance and chrominance components of the colour image in the YCbCr colour space such that the quality of the watermarked image can be better obtained. The simulation results show that the proposed watermarking scheme can effectively proof the tempered region with high detection rate and can restore the tempered region with high quality.