A Complete Image Compression Scheme Based on Overlapped Block Transform with Post-Processing
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A Complete Image Compression Scheme Based on Overlapped Block Transform with Post-Processing C. Kwan,1 B. Li,2 R. Xu,1 X. Li,1 T. Tran,3 and T. Nguyen4 1 Intelligent
Automation, Inc. (IAI), 15400 Calhoun Drive, Suite 400, Rockville, MD 20855, USA of Computer Science and Engineering, Ira. A. Fulton School of Engineering, Arizona State University, P. O. Box 878809, Tempe, AZ 85287-8809, USA 3 Department of Electrical and Computer Engineering, The Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA 4 Department of Electrical and Computer Engineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA 92093-0407, USA 2 Department
Received 29 April 2005; Revised 19 December 2005; Accepted 21 January 2006 Recommended for Publication by Dimitrios Tzovaras A complete system was built for high-performance image compression based on overlapped block transform. Extensive simulations and comparative studies were carried out for still image compression including benchmark images (Lena and Barbara), synthetic aperture radar (SAR) images, and color images. We have achieved consistently better results than three commercial products in the market (a Summus wavelet codec, a baseline JPEG codec, and a JPEG-2000 codec) for most images that we used in this study. Included in the system are two post-processing techniques based on morphological and median filters for enhancing the perceptual quality of the reconstructed images. The proposed system also supports the enhancement of a small region of interest within an image, which is of interest in various applications such as target recognition and medical diagnosis. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
1.
INTRODUCTION
The importance of image compression may be illustrated by the following examples. For TV-quality color image that is 512 × 512 with 24-bit color, it takes 6 million bits to represent the image. For 14 × 17 inch radiograph scanned at 70 micrometer with 12-bit gray scale, it takes about 1200 million bits. If one uses a telephone line with 28,800 baud rate to transmit 1 frame of TV image without compression, it will take 4 minutes, and it will take 11.5 hours to transmit a frame of radiograph. Commonly used image compression approaches such as JPEG use discrete-cosine-transform (DCT)-based transform which introduces annoying block artifacts, especially at high compression ratio, making such approaches undesirable for applications such as target recognition and medical diagnosis. The main objective in this research is to achieve high compression ratios for still images, such as SAR, and color images, without suffering from the annoying blocking artifacts from a JPEG-like coder (DCT-based) or ringing artifacts from wavelet-based codecs (JPEG-2000, e.g.). We aim at building a complete codec that can provide similar
perceptual quality as other algorithms but with a higher compression ratio. Additionally, we also want to provide the flexibility in image transmission with embedded bit
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