Wavelet weighted distortion measure for retinal images

The diagnostic features of retinal images undergo changes in the course of processing such as for storage, retrieval and transmission. The conventional mean square error and peak signal to noise ratio have limitations in quantifying these local distortions. In this work, a novel wavelet weighted distortion measure (WWDM) is proposed for accurate quantification of diagnostic information loss. The wavelet analysis of retinal image shows that the significant information of a retinal feature is captured by a few subbands. The new approach is based on assigning a weight to each of the subbands depending on its diagnostic significance. The proposed distortion measure is defined as the sum of wavelet weighted root of the normalized mean square error of subbands expressed in percentage. The experimental results show that WWDM performs better in capturing the distortion in retinal features, whereas for distortion in clinically nonsignificant regions, it gives a low value. The qualitative evaluation using Pearson linear correlation coefficient and Spearman rank order correlation coefficient is performed for different artifacts. The investigation shows better correlation values between WWDM and the subjective scores.     

Using edge direction information for measuring blocking artifacts of images

Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifacts measurement consistent with subjective rating.     

Removing the blocking artifacts of block-based DCT compressed images

One of the major drawbacks of the block-based DCT compression methods is that they may result in visible artifacts at block boundaries due to coarse quantization of the coefficients. We propose an adaptive approach which performs blockiness reduction in both the DCT and spatial domains to reduce the block-to-block discontinuities. For smooth regions, our method takes advantage of the fact that the original pixel levels in the same block provide continuity and we use this property and the correlation between the neighboring blocks to reduce the discontinuity of the pixels across the boundaries. For texture and edge regions, we apply an edge-preserving smoothing filter. Simulation results show that the proposed algorithm significantly reduces the blocking artifacts of still and video images as judged by both objective and subjective measures.     

Reduction of blocking effect in DCT-coded images based on a visual perception criterion

Blocking effect constitutes one of the main drawbacks of the actual DCT-based compression methods. We propose in this paper a new block reduction technique; it is based on a space-variant non-linear filtering operation of the blocking artifacts present in the image to be reconstructed. To account for the perceptual importance of the distortion, the amount of smoothing is adapted to the visibility of the blocking effect. A visibility parameter is computed for each artifact using the psychovisual properties of the human visual system (HVS). The postprocessing algorithm is in conformity with actual existing compression standards; it provides a way to greatly reduce the artifacts without degrading high-frequency information of the original image. First the proposed method is described and then experimental results are presented, showing the effectiveness of the correction.     

A new image quality assessment method to detect and measure strength of blocking artifacts

Block based transform coding is one of the most popular techniques for image and video compression. However it suffers from several visual quality degradation factors, most notably from blocking artifacts. The subjective picture quality degradation caused by blocking artifacts, in general, does not agree well with the popular objective quality measure such as PSNR.A new image quality assessment method that detects and measures strength of blocking artifacts for block based transform coded images is proposed. In order to characterize the blocking artifacts, we utilize two observations: if blocking artifacts occur on the block boundary, the pixel value changes abruptly across the boundary and the same pixel values usually span along the entire length of the boundary. The proposed method operates only on a single block boundary to detect blocking artifacts. When a boundary is classified as having blocking artifacts, corresponding blocking artifact strength is also computed. Average values of those blocking artifact strengths are converted into a single number representing the subjective image quality. Experiments on various JPEG compressed images with various bit rates demonstrated that the proposed blocking artifacts measuring value matches well with the subjective image quality judged by human observers.     

GridSAR: Grid strength and regularity for robust evaluation of blocking artifacts in JPEG images

Images are subject to blocking artifacts when they are compressed using the JPEG standard. Knowing the extent of blocking artifacts is thus necessary for such applications as automatic quality monitoring and restoration. The current blocking artifacts measures are based on a strong prior that the block boundaries are known in advance, which often does not hold in real-world applications. Therefore, their performances degrade significantly when block boundaries are misaligned. To address the problem, this paper presents a robust no-reference blocking artifacts evaluation metric for JPEG images based on grid strength and regularity (GridSAR). The underlying idea is to extract block grids from a JPEG image and quantify the grid image to evaluate the strength of blocking artifacts. To this end, a grid map of blocking artifacts is first extracted from the image in the spatial domain. Then the blocking artifacts of the image are evaluated by quantifying the strength and regularity of the grid image. Furthermore, in order to account for the varying sensitivities of human eyes to the blocking artifacts in smooth and textured areas, a masking function is also proposed. Experimental results on seven popular image quality databases demonstrate that GridSAR achieves the state-of-the-art performance, and is robust to block misalignments.     

Quality measure of color images based on properties ofvision psychology and color distortion in MPEG-21

In this article, a new way to evaluate the quality of color images is proposed, in which the properties of human vision psychology, objective fidelity, edge information, and color distortion will be combined through utilizing 3-D matrix transform. There exists color redundancy and structural similarity between three different frames of a color image, the definition of vision properties will be measured by 3-D submatrix integration transform (SIT), in which three color components are integrated into one model and color redundancy can be exploited fully. The simulation results show that the measure index is very effective and objective in accord with vision properties.     

Postprocessing technique for blocking artifacts reduction in DCT domain

An effective post-processing technique is proposed to reduce the blocking artifacts in the block discrete cosine transform (BDCT)-coded images. Simulation results indicate that the proposed scheme outperforms conventional post-processing techniques in both PSNR and visual quality.     

Detection of blocking artifacts in compressed video

A novel algorithm for the detection of artifacts in compressed video is described. The algorithm does not require access to the original video and therefore can be very useful in situations where quality assessment needs to be carried out at the receiver end. The proposed method is insensitive to other common video artifacts such as blurring for similar levels of objective distortion. The use of fast transformations in the frequency domain makes the method attractive for real-time applications     

A new method for distortion correction of electronic endoscope images

A new method to correct the barrel distortion of an electronic endoscope image is presented. A correction model assuming circularly symmetric distortion is introduced with the following model parameters: the center of distortion and the coefficients of polynomials representing the distortion correction in the radial direction. If the imaging system is distortion-free, straight lines in the object space should be imaged as straight lines. Based on this criterion, a distorted image of a standard pattern consisting of a grid of several straight lines is recorded, and the model parameters are then estimated as a basis for straightening distorted lines. This method has the advantage of not needing a careful placement of the standard pattern for calibration. Correction results are presented for the grid pattern chart to verify a sufficient degree of correction. Examples of distortion correction of real intestinal images and physicians' comments are also presented.     

A Bayesian approach for the estimation and transmission ofregularization parameters for reducing blocking artifacts

With block-based compression approaches for both still images and sequences of images annoying blocking artifacts are exhibited, primarily at high compression ratios. They are due to the independent processing (quantization) of the block transformed values of the intensity or the displaced frame difference. We propose the application of the hierarchical Bayesian paradigm to the reconstruction of block discrete cosine transform (BDCT) compressed images and the estimation of the required parameters. We derive expressions for the iterative evaluation of these parameters applying the evidence analysis within the hierarchical Bayesian paradigm. The proposed method allows for the combination of parameters estimated at the coder and decoder. The performance of the proposed algorithms is demonstrated experimentally.     

Correction of distortion in endoscope images

Images formed with endoscopes suffer from a spatial distortion due to the wide-angle nature of the endoscope's objective lens. This change in the size of objects with position precludes quantitative measurement of the area of the objects, which is important in endoscopy for accurately measuring ulcer and lesion sizes over time. A method for correcting the distortion characteristic of endoscope images is presented. A polynomial correction formula was developed for the endoscope lens and validated by comparing quantitative test areas before and after the distortion correction. The distortion correction has been incorporated into a computer program that could readily be applied to electronic images obtained at endoscopy using a desk-top computer. The research presented here is a key step towards the quantitative determination of the area of regions of interest in endoscopy.     

Wavelet based watermarking method for digital images using thehuman visual system

A wavelet based multiresolution watermarking method using the human visual system (HVS) is proposed, with the number of watermarks embedded proportional to the energy contained in each band. Experiments show that the proposed three-level wavelet based watermarking method is robust to some attacks such as, for example, joint photographic experts group (JPEG) compression, smoothing, cropping and collusion     

Objective distortion measure for binary text image based on edge line segment similarity.

This paper proposes a new approach to measure the distortion introduced by changing individual edge pixels in binary text images. The approach considers not only how many pixels are changed but also where the pixels are changed and how the flipping affects the overall shape formed by the edge line. Similarities between the edge line segments in the original and distorted image are compared to measure the distortion. Subjective testing shows that the new distortion measure correlates well with human visual perception.     

Fixed distortion subband coding of images for packet-switchednetworks

A subband image codec is presented that approximately attains a user-prescribed fidelity by allowing the encoder's compression rate to vary. The fixed distortion subband coding (FDSBC) system is suitable for use with future of packet-switched networks. The codec's design is based on an algorithm that allocates distortion among the subbands to minimize channel entropy. By coupling this allocation procedure with judiciously selected subband quantizers, an elementary four-band codec was obtained. Additional four-band structures may be nested in a hierarchical configuration for improved performance. Each of the configurations tested attains mean square distortions within 2.0 dB of the user-specific value over a wide range of distortion for several standard test images. Rate versus mean-square distortion performance rivals that of fixed-rate systems having similar complexity. The encoder's output is formatted to take advantage of prioritized packet networks. Simulations show that FDSBC is robust with respect to packet loss and may be used effectively for progressive transmission applications     

Reconstruction error distortion measure for quantisation of LPCmodels

A new distortion measure is proposed for the quantisation of an LPC model. It has a time-domain interpretation, entirely different from that of conventional distortion measures, such as spectral distortion and likelihood ratio. Experimental results indicate that five bits/frame may be gained, without loss of quality     

Noise-assisted correlation algorithm for suppressing noise-induced artifacts in ultrasonic Nakagami images

Ultrasonic Nakagami images can complement conventional B-mode images for scatterer characterization. White noise in anechoic areas leads to artifacts that affect the Nakagami image to characterize tissues. Artifact removal requires rejection of the white noise without deforming the backscattered waveform. This study proposes a noise-assisted correlation algorithm (NCA) and carries out simulations, phantom experiments, and clinical measurements to validate its feasibility and practicality. The simulation results show that the NCA can reject white noise in an anechoic area without any deformation of the backscattered waveforms. The results obtained from phantoms and tissues further demonstrate that the proposed NCA can suppress a Nakagami image artifact without changing the texture of the Nakagami image of the scattering background. The NCA is an essential algorithm to construct artifact-free Nakagami image for correctly reflecting scatterer properties of biological tissues.     

Method for crosscorrelating images in the presence of geometric distortion

The conventional crosscorrelation function (XCF) used in temporal and spatial displacement measurement is unable to provide satisfactory results when linear distortion is also present in the signals. A 'nested' correlation function (NCF) is proposed which produces accurate results, when the distortion is dispersive, with negligible computational overhead.<>     

植基于人类视觉系统之二色调图像信息隐藏技术

二色调图像（halftone image）是一种非常特殊的黑白图像，即在一定的距离观看它时，二色调图像仍具有灰阶图像的视觉效果。此种图像被广泛地使用在新闻报纸或杂志中。本文提出了一个利用了人类视觉特性的方法，有效地将机密信息隐藏在二色调图像中，实验结果显示此方法具有很高的实用价值。     

Tree encoding for symmetric sources with a distortion measure

A simple algorithm is developed for mapping the outputs of a source into the set of code sequences generated by a tree code. The algorithm is analyzed for a special case in which the source produces discrete independent equiprobable letters, and the distortion measure satisfies a symmetry condition. LettingRbe the code rate andD^{ast}be the minimum average distortion for that rate as given by Shannon's rate-distortion theorem, we show that the algorithm is capable of achieving average distortion as close toD^{ast}as desired. Furthermore an upper bound is developed on the average amount of computation for the algorithm. Asymptotically as the average distortionapproaches the theoretical limitD^{ast}, the bound on average computation has the formexp [a/ sqrt{ - D^{ast} }]for some constanta.