Ping-Sing Tsai

JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures

Preface.1. Introduction to Data Compression.2. Source Coding Algorithms.3. JPEG-Still Image Compression Standard.4. Introduction to Discrete Wavelet Transform.5. VLSI Architectures for Discrete Wavelet Transforms.6. JPEG 2000 Standard.7. Coding Algorithms in JPEG 2000.8. Code Stream Organization and File Format.9. VLSI Architectures for JPEG 2000.10. Beyond Part 1. of JPEG 2000.Index.About the Authors.

Adaptive fuzzy color interpolation

In an electronic color imaging device, such as a digital camera, using a single CCD or CMOS sensor, the color information is usually acquired in sub-sampled patterns of Red (R), Green (G) and Blue (B) pixels. Full resolution color is subsequently generated from this sub-sampled image. This is popularly called Color Interpolation or Color Demosaicing. In this paper, we present a color interpolation algorithm using a method of fuzzy membership assignment along with the concept of smooth hue transition. The algorithm is adaptive in nature and produces superior quality full resolution color images compared to most of the popularly known color interpolation algorithms in the literature. We present the results of comparison with some challenging sub-sampled images for color interpolation.

Rate-distortion optimization algorithm for JPEG 2000

A novel rate-distortion optimization algorithm for JPEG 2000 is proposed. This algorithm meets memory buffer requirement for the compressed bit streams quite strictly according to a given bit rate. Moreover, before the encoding process even starts, a required memory buffer size can be estimated. This algorithm can also help avoid unnecessary encoding for some parts of an image. In this sense, it is memory efficient and performs progressive encoding. While a rate-distortion optimization algorithm is generally applied after complete encoding procedures for images in JPEG 2000, the proposed algorithm can save both memory requirement and encoding time significantly at low bit rate by avoiding complete encoding.

Fuzzy-assignment-based color interpolation algorithm

In an electronic color imaging device such as a digital camera using a single CCD or CMOS sensor, the color information is usually acquired in sub-sampled patterns of red (R), green (G) and blue (B) pixels. Full resolution color is subsequently generated from this sub-sampled image. This is popularly called Color Interpolation or Color Demosaicing. In this paper, we present a color interpolation algorithm using the method of fuzzy membership assignment along with the concept of smooth hue transition. The algorithm is adaptive in nature and produces superior quality full resolution color images compared to most of the popularly known color interpolation algorithms in the literature. Performance of the algorithm has been compared with a previously proposed block matching algorithm for color interpolation by the authors as well as the popularly used bilinear color interpolation. We present the results of comparison with some challenging sub-sampled images for color interpolation.