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Image compression using Hybrid DWT & DCT. Presented by: Suchitra Shrestha Department of Electrical and Computer Engineering Date: 2008/10/09. Introduction(1). Why Image Compression? Digital images in their raw form require an enormous amount of memory To reduce Redundancy
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Image compression using Hybrid DWT & DCT Presented by: Suchitra Shrestha Department of Electrical and Computer Engineering Date: 2008/10/09
Introduction(1) • Why Image Compression? • Digital images in their raw form require an enormous amount of memory • To reduce Redundancy • To increase transmission bandwidth • To reduce storage capacity
Introduction (2) • Techniques • Discrete Cosine Transform (DCT) • “blocking artifacts” occurring at block boundaries particularly at low bit rates • Discrete Wavelet Transform (DWT) • image is transformed &compressed as a single data object rather than block-by-block • uniform distribution of compression error across the entire image • can provide better image quality
Motivations and Objectives • Most of the previous papers consider either DCT or DWT • Application of hybrid DWT-DCT transform algorithm • combined transforms compensate for the drawbacks of each other • result in an effective image processing. • improved Peak Signal to Noise Ratio (PSNR)
Methodology • Application of a two dimensional DWT over the image of size 16 by 16 • Quantization • DCT • Inverse the process • PSNR Comparison to demonstrate the performance of proposed algorithm • Application of the proposed algorithm in applications • Medical imaging • Water marking • Tele-medicine