Local Band-limited Contrast Research Articles

Multifocus image fusion and depth reconstruction

The acquisition of sharp, full-focus images and the restoration of microscopic scenes require complex instrumentation and algorithms. To conveniently obtain the three-dimensional (3-D) structural information of full-focus images and high-quality microscopic scenes, we construct a zoomable 3-D microscope imaging system and propose new image fusion and depth reconstruction algorithms based on this imaging system. The image acquisition environment of the system is analyzed using interference factors such as light transmission variation and jitter, and the corresponding image preprocessing methods are discussed. We combined the new sum-modified-Laplacian (SML) and local band-limited contrast methods, which contain multiple image features but measure the image definition from different angles, then proposed a mixed-contrast factor, and combined it with the SML method to propose an image fusion method. We then proposed a depth reconstruction method based on the structural similarity of multifocus images. For cases where depth reconstruction results in large distortion with high noise, we proposed a depth value restoration method based on anisotropic diffusion to improve the 3-D reconstruction results. Experimental results show that the proposed image fusion and depth reconstruction methods exhibit excellent performance.

An Improved Image Contrast Assessment Method

Contrast is an important factor affecting the image quality. In order to overcome the problems of local band-limited contrast, a novel image contrast assessment method based on the property of HVS is proposed. Firstly, the image by low-pass filter is performed fast wavelet decomposition. Secondly, all levels of band-pass filtered image and its corresponding low-pass filtered image are obtained by processing wavelet coefficients. Thirdly, local band-limited contrast is calculated, and the local band-limited contrast entropy is calculated according to the definition of entropy, Finally, the contrast entropy of image is obtained by averaging the local band-limited contrast entropy weighed using CSF coefficient. The experiment results show that the best contrast image can be accurately identified in the sequence images obtained by adjusting the exposure time and stretching gray respectively, the assessment results accord with human visual characteristics and make up the lack of local band-limited contrast. DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.3719 Full Text: PDF

An Improved Image Contrast Assessment Method

Contrast is an important factor affecting the image quality. In order to overcome the problems of local band-limited contrast, a novel image contrast assessment method based on the property of HVS is proposed. Firstly, the image by low-pass filter is performed fast wavelet decomposition. Secondly, all levels of band-pass filtered image and its corresponding low-pass filtered image are obtained by processing wavelet coefficients. Thirdly, local band-limited contrast is calculated, and the local band-limited contrast entropy is calculated according to the definition of entropy. Finally, the contrast entropy of image is obtained by averaging the local band-limited contrast entropy weighed using CSF coefficient. The experiment results show that the best contrast image can be accurately identified in the sequence images obtained by adjusting the exposure time and stretching gray respectively, the assessment results accord with human visual characteristics and make up the lack of local band-limited contrast.

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.

Visual Coding: Design of Psychovisual Quantizers

This paper describes a new methodology in the design of psychovisual quantizers for a given visual subband image coding scheme. The quantizer design needs to specify a set of decision thresholds (Tk,k= 0, . . . ,l) and reconstruction levels (Lk,k= 0, . . . ,l− 1) for which any input level lying between the thresholdsTkandTk+1is mapped toLk, thekth reconstruction level. To specify the optimal quantization, psychophysical experiments based on the visibility of quantization noise have been conducted. The contrast masking function has been determined by considering complex signals, spatial frequency aspects of the quantized signals, and the spatial combination of degradations. The stimuli used have been characterized by their local band-limited contrast. With this representation, within a subband, the first important result is that the decision thresholds and the reconstruction levels of the quantization follow a linear law regardless of the importance of the contrast. From one subband to another the quantization step varies according to radial spatial frequency and orientation. In order to examine the masking effects between subbands, further experiments have been conducted and two other important results have been obtained. First, when it occurs, masking does not modify the linear behavior of the optimal quantization law. Secondly, masking is due to the adjacent angular subbands rather than the adjacent radial ones, even if a slight increase in the quantization step is observed in this last case.

In search of a contrast metric: matching the perceived contrast of Gabor patches at different phases and bandwidths.

The definition of contrast in a complex scene is a long-standing problem. The local contrast in an image may be approximated by the contrast of a Gabor patch of varying phase and bandwidth. Observers' perceived (apparent) contrast, as indicated by matching of such patterns, were compared here to the physical contrast calculated by a number of definitions. The 2 c/deg 1-octave Gabor patch stimuli of different phases were presented side by side, separated by 4 deg. During each session the subjects (n = 5) were adapted to the average luminance, and four different contrast levels were randomly interleaved. The subject's task was to indicate which of the two patterns was lower in contrast. Equal apparent contrast was determined by fitting a psychometric function to the data. The results of the matching rejected the hypothesis that either the Michelson formula or the King-Smith and Kulikowski contrast metric (CKK = (Lmax-Lbackground)/Lbackground) was used by the subjects to set the matching. The use of the Nominal contrast (the Michelson contrast of the underlying sinusoid) as an estimate of apparent contrast could not be rejected. In a second experiment the apparent contrast of a 1-octave Gabor patch was matched to the apparent contrast of a 2-octave Gabor patch (of Nominal contrast of 0.1, 0.3, 0.6, 0.8) using the method of adjustment. The results of this experiment disagree with the prediction of the Nominal contrast definition as well. The local band-limited contrast measure (Peli, 1990), when used with the modifications suggested by Lubin (1995) as an estimate of apparent contrast, could not be rejected by the results of either experiment. These results suggest that a computational contrast metric based on multi-scale bandpass filtering is a better estimate of apparent perceived contrast than any of the other metrics tested.

Contrast in complex images

The physical contrast of simple images such as sinusoidal gratings or a single patch of light on a uniform background is well defined and agrees with the perceived contrast, but this is not so for complex images. Most definitions assign a single contrast value to the whole image, but perceived contrast may vary greatly across the image. Human contrast sensitivity is a function of spatial frequency; therefore the spatial frequency content of an image should be considered in the definition of contrast. In this paper a definition of local band-limited contrast in images is proposed that assigns a contrast value to every point in the image as a function of the spatial frequency band. For each frequency band, the contrast is defined as the ratio of the bandpass-filtered image at the frequency to the low-pass image filtered to an octave below the same frequency (local luminance mean). This definition raises important implications regarding the perception of contrast in complex images and is helpful in understanding the effects of image-processing algorithms on the perceived contrast. A pyramidal image-contrast structure based on this definition is useful in simulating nonlinear, threshold characteristics of spatial vision in both normal observers and the visually impaired.