Properties Of Human Visual System Research Articles

Research on wavelet-based algorithm for image contrast enhancement

A novel wavelet-based algorithm for image enhancement is proposed in the paper. On the basis of multiscale analysis, the proposed algorithm solves efficiently the problem of noise over-enhancement, which commonly occurs in the traditional methods for contrast enhancement. The decomposed coefficients at same scales are processed by a nonlinear method, and the coefficients at different scales are enhanced in different degree. During the procedure, the method takes full advantage of the properties of Human visual system so as to achieve better performance. The simulations demonstrate that these characters of the proposed approach enable it to fully enhance the content in images, to efficiently alleviate the enhancement of noise and to achieve much better enhancement effect than the traditional approaches.

Watermarking Sites Selection Based on a Human Visual Model

This article presents a new approach in the selection of auspicious sites to be watermarked. The selection takes into account human visual system properties including luminance adaptation, contrast sensitivity and spatio-frequential selectivity. This article exploits also the local band limited contrast to determine the maximum watermark strength to be applied without inducing visible degradations. Compared to the well-known approaches, a contrast masking model is used here to adjust, site by site, the watermark strength. To test the approach efficiency, obtained results are considered in the context of an adaptive watermarking algorithm. The performance of this latter is evaluated in terms of watermark invisibility and robustness. Watermark invisibility is judged through subjective tests conducted with three observers according to the CCIR recommendations. Original watermark detection results are also presented to analyze the robustness of the scheme to most common attacks such as JPEG compression, cropping (with zero padding) and blur.

Design and Evaluation of an Entirely Psychovisual-Based Coding Scheme

In this paper a new psychovisual-based coding scheme is proposed. The analysis and the quantization stages, the two main functions which determine the performances of a coding scheme, are based on the human visual system properties. In the first stage, a filter bank decomposes images into subimages of perceptual significance when a contrast transformation is applied. Analytic cortex filters have been used because they provide an accurate modelization of visual receptive fields. The choice of subbands lies on psychovisual experiments led in the laboratory. It was found that visual information is processed through 17 channels. In the second stage the use of the local band-limited contrast yields very interesting properties concerning the quantization. A scalar and vector quantization have been considered. In this latter case the vector's construction methodology preserves the main properties of the human visual system about perception of quantization impairments and takes into account the masking effect due to interaction between subbands with the same radial frequency but with different orientations. The vector's components are the local band limited contrasts Cij (m, n) defined as the ratio between the luminance Lij at the point (m, n), which belongs to the radial subband i and angular sector j and the average luminance at this location. Hence the vector's dimension depends on the orientation selectivity of the chosen decomposition. The low pass subband, which is nondirectional is scalar quantized. A methodology for automatic subsampling matrix design was also developed. The performance have been evaluated on a set of images in terms of peak SNR, true bit rates, and visual quality. For the latter, no impairments are visible at a distance of four times the height of the used high quality TV monitor. The SNRs are about 6 to 8 dB under the ones of classical subband image coding schemes when producing the same visual quality. Another particularity of this approach, due to the use of the local band limited contrast, lies in the structure of the reconstruction image error which is found to be highly correlated to the structure of the original image.

Adaptive local contrast enhancement method for medical images displayed on a video monitor

It is known that light-box luminance is an important factor in the detection of objects on radiographs. Existing methods for image contrast enhancement do not consider the luminance effect so that the enhancement may be inappropriate for the processed image displayed on a video monitor. Based on the properties of human visual system (HVS), an adaptive local contrast enhancement (ALCE) method was developed to enhance the medical image displayed on the video monitor by investigating the influence on human eyes of display luminance difference between a conventional light-box and a video monitor. The HVS model indicated parts of a radiograph unclear to human eyes at a given display luminance. By calculating the contrast of the image pixel by pixel, we found the parts of an image that are needed to be amplified at low display luminance and provided these parts with adequate enhancement. The processed image displayed on a video monitor was visually equivalent to the raw radiograph displayed on a light-box. A quantitative evaluation method of image quality assessment was used to compare the ALCE-processed image with others.

A Haar Wavelet Approach to Compressed Image Quality Measurement

The traditional mean-squared-error and peak-signal-to-noise-ratio error measures are mainly focused on the pixel-by-pixel difference between the original and compressed images. Such metrics are improper for subjective quality assessment, since human perception is very sensitive to specific correlations between adjacent pixels. In this work, we explore the Haar wavelet to model the space–frequency localization property of human visual system (HVS) responses. It is shown that the physical contrast in different resolutions can be easily represented in terms of wavelet coefficients. By analyzing and modeling several visual mechanisms of the HVS with the Haar transform, we develop a new subjective fidelity measure which is more consistent with human observation experience.

Perceptually tuned robust watermarking scheme for digital images

In this paper, we present a digital image watermarking scheme that uses both human visual system and statistical properties. The scheme places watermark in discrete cosine transform (DCT) domain and spreads the watermark effect on the entire image. We have compared our proposed scheme with two other popular schemes and shown that our proposed scheme yields better results in terms of transparency, robustness and maximal capacity requirements.

Human Visual System Based Wavelet Decomposition for Image Compression

Due to limitations in bandwidth or storage space, many applications require compression of digital images. One of the main hindrances to progress in the area of image communications is the large amount of information contained in an image. In this paper, we propose a wavelet-based image compression technique which incorporates some of the properties of the human visual system (HVS). A new wavelet decomposition based on the HVS will be introduced. The wavelet coefficients will be quantized with a vector quantization technique which uses HVS properties to allocate bits to the various subbands. The new HVS-based wavelet decomposition will be compared with the existing separable and nonseparable wavelet decompositions. Compression techniques based on such considerations yield higher quality results compared to standard techniques. Several experimental results will be shown.

Letter: Treatment of singularity for spatial transfer properties of human visual system at threshold.

Letter: Treatment of singularity for spatial transfer properties of human visual system at threshold.