Generalized Triangular Decomposition in Transform Coding

A general family of optimal transform coders (TCs) is introduced here based on the generalized triangular decomposition (GTD) developed by Jiang This family includes the Karhunen-Loeve transform (KLT) and the generalized version of the prediction-based lower triangular transform (PLT) introduced by Phoong and Lin as special cases. The coding gain of the entire family, with optimal bit allocation, is equal to that of the KLT and the PLT. Even though the original PLT introduced by Phoong is not applicable for vectors that are not blocked versions of scalar wide sense stationary processes, the GTD-based family includes members that are natural extensions of the PLT, and therefore also enjoy the so-called MINLAB structure of the PLT, which has the unit noise-gain property. Other special cases of the GTD-TC are the geometric mean decomposition (GMD) and the bidiagonal decomposition (BID) transform coders. The GMD-TC in particular has the property that the optimum bit allocation is a uniform allocation; this is because all its transform domain coefficients have the same variance, implying thereby that the dynamic ranges of the coefficients to be quantized are identical

Perceptually-Driven Video Coding with the Daala Video Codec

The Daala project is a royalty-free video codec that attempts to compete with the best patent-encumbered codecs. Part of our strategy is to replace core tools of traditional video codecs with alternative approaches, many of them designed to take perceptual aspects into account, rather than optimizing for simple metrics like PSNR. This paper documents some of our experiences with these tools, which ones worked and which did not. We evaluate which tools are easy to integrate into a more traditional codec design, and show results in the context of the codec being developed by the Alliance for Open Media.Comment: 19 pages, Proceedings of SPIE Workshop on Applications of Digital Image Processing (ADIP), 201

Theory of optimal orthonormal subband coders

The theory of the orthogonal transform coder and methods for its optimal design have been known for a long time. We derive a set of necessary and sufficient conditions for the coding-gain optimality of an orthonormal subband coder for given input statistics. We also show how these conditions can be satisfied by the construction of a sequence of optimal compaction filters one at a time. Several theoretical properties of optimal compaction filters and optimal subband coders are then derived, especially pertaining to behavior as the number of subbands increases. Significant theoretical differences between optimum subband coders, transform coders, and predictive coders are summarized. Finally, conditions are presented under which optimal orthonormal subband coders yield as much coding gain as biorthogonal ones for a fixed number of subbands

Quality and Rate Control of JPEG XR

Driven by the need for seismic data compression with high dynamic range and 32-bit resolution, we propose two algorithms to efficiently and precisely control the signal-to-noise ratio (SNR) and bit rate in JPEG XR image compression to allow users to compress seismic data with a target SNR or a target bit rate. Based on the quantization properties of JPEG XR and the nature of blank macroblocks, we build a reliable model between the quantization parameter (QP) and SNR. This enables us to estimate the right QP with target quality for the JPEG XR encoder

Modeling and synthesis of the HD photo compression algorithm

The primary goal of this thesis is to implement the HD Photo encoding algorithm using Verilog HDL in hardware. The HD Photo algorithm is relatively new and offers several advantages over other digital still continuous tone image compression algorithms and is currently under review by the JPEG committee to become the next JPEG standard, JPEG XR. HD Photo was chosen to become the next JPEG standard because it has a computationally light domain change transform, achieves high compression ratios, and offers several other improvements like its ability to supports a wide variety of pixel formats. HD Photo’s compression algorithm has similar image path to that of the baseline JPEG but differs in a few key areas. Instead of a discrete cosine transform HD Photo leverages a lapped biorthogonal transform. HD Photo also has adaptive coefficient prediction and scanning stages to help furnish high compression ratios at lower implementation costs. In this thesis, the HD Photo compression algorithm is implemented in Verilog HDL, and three key stages are further synthesized with Altera’s Quartus II design suite with a target device of a Stratix III FPGA. Several images are used for testing for quality and speed comparisons between HD Photo and the current JPEG standard using the HD Photo plug-in for Adobe’s Photoshop CS3. The compression ratio when compared to the current baseline JPEG standard is about 2x so the same quality image can be stored in half the space. Performance metrics are derived from the Quartus II synthesis results. These are approximately 108,866 / 270,400 ALUTs (40%), a 10 ns clock cycle (100 MHz), and a power estimate of 1924.81 mW

Biorthogonality in lapped transforms : a study in high-quality audio compression

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 76-82).by Shiufun Cheung.Ph.D

A Wavelet Visible Difference Predictor

In this paper, we describe a model of the human visual system (HVS) based on the wavelet transform. This model is largely based on a previously proposed model, but has a number of modifications that make it more amenable to potential integration into a wavelet based image compression scheme. These modifications include the use of a separable wavelet transform instead of the cortex transform, the application of a wavelet contrast sensitivity function (CSF), and a simplified definition of subband contrast that allows us to predict noise visibility directly from wavelet coefficients. Initially, we outline the luminance, frequency, and masking sensitivities of the HVS and discuss how these can be incorporated into the wavelet transform. We then outline a number of limitations of the wavelet transform as a model of the HVS, namely the lack of translational invariance and poor orientation sensitivity. In order to investigate the efficacy of this wavelet based model, a wavelet visible difference predictor (WVDP) is described. The WVDP is then used to predict visible differences between an original and compressed (or noisy) image. Results are presented to emphasize the limitations of commonly used measures of image quality and to demonstrate the performance of the WVDP. The paper concludes with suggestions on how the WVDP can be used to determine a visually optimal quantization strategy for wavelet coefficients and produce a quantitative measure of image quality

Advanced Telecommunications and Signal Processing Program

Contains an introduction and reports on twelve research projects.AT&T FellowshipAdvanced Telecommunications Research ProgramINTEL FellowshipU.S. Navy - Office of Naval Research NDSEG Graduate FellowshipMaryland Procurement Office Contract MDA904-93-C-418

Results on optimal biorthogonal filter banks

Optimization of filter banks for specific input statistics has been of interest in the theory and practice of subband coding. For the case of orthonormal filter banks with infinite order and uniform decimation, the problem has been completely solved in recent years. For the case of biorthogonal filter banks, significant progress has been made recently, although a number of issues still remain to be addressed. In this paper we briefly review the orthonormal case, and then present several new results for the biorthogonal case. All discussions pertain to the infinite order (ideal filter) case. The current status of research as well as some of the unsolved problems are described