Han Oh

Visually Lossless Encoding for JPEG2000

Due to exponential growth in image sizes, visually lossless coding is increasingly being considered as an alternative to numerically lossless coding, which has limited compression ratios. This paper presents a method of encoding color images in a visually lossless manner using JPEG2000. In order to hide coding artifacts caused by quantization, visibility thresholds (VTs) are measured and used for quantization of subband signals in JPEG2000. The VTs are experimentally determined from statistically modeled quantization distortion, which is based on the distribution of wavelet coefficients and the dead-zone quantizer of JPEG2000. The resulting VTs are adjusted for locally changing backgrounds through a visual masking model, and then used to determine the minimum number of coding passes to be included in the final codestream for visually lossless quality under the desired viewing conditions. Codestreams produced by this scheme are fully JPEG2000 Part-I compliant.

Visibility thresholds for quantization distortion in JPEG2000

Visibility thresholds play an important role in finding appropriate quantization step sizes in image and video compression systems. In this paper we present a new method of measuring visibility thresholds for quantization distortion in JPEG2000. A quantization distortion model for each subband is developed based on the statistical characteristics of wavelet coefficients and the dead-zone quantizer of JPEG2000. Thresholds obtained from these quantization distortion models are image-adaptive and ensure visually lossless coding with low computational burden.

View Compensated Compression of Volume Rendered Images for Remote Visualization

Remote visualization of volumetric images has gained importance over the past few years in medical and industrial applications. Volume visualization is a computationally intensive process, often requiring hardware acceleration to achieve a real time viewing experience. One remote visualization model that can accomplish this would transmit rendered images from a server, based on viewpoint requests from a client. For constrained server-client bandwidth, an efficient compression scheme is vital for transmitting high quality rendered images. In this paper, we present a new view compensation scheme that utilizes the geometric relationship between viewpoints to exploit the correlation between successive rendered images. The proposed method obviates motion estimation between rendered images, enabling significant reduction to the complexity of a compressor. Additionally, the view compensation scheme, in conjuction with JPEG2000 performs better than AVC, the state of the art video compression standard.

Multi-resolution visually lossless image coding using JPEG2000

The visibility threshold is the maximum contrast where a stimulus remains invisible. This value varies with the spatial frequency and orientation of the stimulus and is often used in determining the quantization step size of a subband for visually lossless coding. When an image is displayed at a different resolution level, the spatial frequency of each subband is also changed. Previous JPEG2000 visually lossless algorithms have a single set of quantization step sizes optimized for the full display resolution. This implies that if the image is rendered at reduced resolution there are significant amounts of extraneous information in the codestream. In this paper we present a new coding method which effectively incorporates multiple quantization step sizes into the JPEG2000 framework. This allows for visually lossless decoding at a variety of resolutions, using only a portion of the full resolution codestream.

Video compressed sensing using iterative self-similarity modeling and residual reconstruction

Abstract. Compressed sensing (CS) has great potential for use in video data acquisition and storage because it makes it unnecessary to collect an enormous amount of data and to perform the computationally demanding compression process. We propose an effective CS algorithm for video that consists of two iterative stages. In the first stage, frames containing the dominant structure are estimated. These frames are obtained by thresholding the coefficients of similar blocks. In the second stage, refined residual frames are reconstructed from the original measurements and the measurements corresponding to the frames estimated in the first stage. These two stages are iterated until convergence. The proposed algorithm exhibits superior subjective image quality and significantly improves the peak-signal-to-noise ratio and the structural similarity index measure compared to other state-of-the-art CS algorithms.

Visually lossless JPEG2000 at fractional resolutions

JPEG2000 images with K wavelet decomposition levels inherently support K + 1 spatial resolutions. Other resolutions can be obtained through resampling adjacent native resolution images. In this paper, we propose a method of encoding images that can be decoded at arbitrary resolutions in a visually lossless manner with minimum bitrates. To achieve this, visibility thresholds for resampled quantization distortions are studied, and a technique of applying thresholds that vary with the display resolution is introduced.

Visually lossless JPEG2000 using adaptive visibility thresholds and visual masking effects

This paper proposes a method of encoding images in a visually lossless manner using adaptive visibility thresholds and visual masking effects within the framework of JPEG2000. Our adaptive visibility thresholds (VTs) are determined through psychophysical experiments for measuring quantization distortion models, which are based on the variance of wavelet coefficients and the characteristics of the deadzone quantizer of JPEG2000. These VTs are further adjusted using visual masking effects present in the background image where distortion appears, and are used to determine the quantization level in the embedded bit-plane coder for visually lossless coding. The proposed method modifies the distortion calculation and codestream generation stages in the encoder and the resulting codestreams are fully compatible with Part-I of the JPEG2000. Compared with numerically lossless compression of JPEG2000, the proposed method achieves a 60% reduction in bitrate without visual quality degradation. Also, the proposed method yields superior image quality at equivalent bitrates, compared with conventional JPEG2000 encoders.

Visually Lossless JPEG 2000 for Remote Image Browsing

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of (spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting (multiple) quantization step sizes into a single JPEG2000 codestream. This codestream is JPEG2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG2000 Interactive Protocol (JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results.

Super resolution reconstruction based on block matching and three-dimensional filtering with sharpening

Super resolution (SR) reconstruction is often considered to be an inverse problem in the sense that unknown high resolution images are sought for giving low resolution images. Recent studies have shown that the sparsity regularisation used in compressed sensing (CS) reconstruction improves the performance of SR reconstruction. Furthermore, under the assumption that mutually similar regions exist within a natural image, non-local (NL) estimation produces accurate estimates for given degraded images. The incorporation of this NL estimation in SR reconstruction has been shown to yield better reconstructions. In this study, the authors propose the use of block matching and three-dimensional filtering with sharpening estimation as the regularisation constraint under the CS-based SR framework. This estimation collects similar blocks and adaptively filters them by the shrinkage of the transform coefficients. It recovers detailed structures while attenuating ringing artefacts. In addition, a sharpening technique used in the estimation also emphasises edges. As a result, the proposed SR algorithm searches for the solution that is similar to this enhanced estimate from among all feasible solutions. The experimental results demonstrate that the proposed method provides high-quality SR images, both numerically and subjectively.

Hill climbing algorithm for the transmission of layered jpeg2000 video under multiple rate constraints

Video transmission is a topic of major interest in our community. One of the most fundamental aspects behind many video transmission schemes is the bit allocation problem that occurs when variable bitrate video is transmitted under multiple rate constraints. Rate constraints are imposed by the channel capacity, buffer sizes in the server and/or client, and by the coding system. This work introduces a rate allocation method conceived from hill climbing techniques with steepest descent that requires very few computational resources. Experimental results achieved within the framework of JPEG2000 suggest that our approach commonly achieves a solution close to the global optimum.