Fractal Image Encoding Using Fringe Based Property

Indu Aggarwal

ISBN 10: 365991939X / ISBN 13: 9783659919398

Published by LAP Lambert Academic Publishing, 2016

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Fractal image encoding is one of the famous lossy encoding techniques ascertain high compression ratio, higher PSNR and good quality of encoded image. It is the approach that uses self similarity property in natural image.The main drawback of fractal image encoding is time consumption in search of appropriate domain for each range of image blocks.There have been various researches carried out to overcome the limitation of fractal encoding and to speed up the encoder.The neighborhood search strategy used in spatial domain reduces the encoding time from linear time to logarithmic time.The proposed algorithm used k-nearest neighbor search to find the similar edge shaped range and domain blocks to be mapped on the basis of DCT lowest coefficients in horizontal and vertical directions and then using similarity measure; the virtual codebook was prepared to encode the image and then decoded the image using averaging of pixels of selected domains. The proposed approach explained in this book is compared with the existing method and this work gave high PSNR value, high compression ratio and reduced MSE computations with little decay in image quality which is acceptable.

Seller Inventory # 9783659919398

Bibliographic Details

• Title: Fractal Image Encoding Using Fringe Based Property
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 365991939X
• ISBN 13: 9783659919398
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 125 grams

About this title

Synopsis

Fractal image encoding is one of the famous lossy encoding techniques ascertain high compression ratio, higher PSNR and good quality of encoded image. It is the approach that uses self similarity property in natural image.The main drawback of fractal image encoding is time consumption in search of appropriate domain for each range of image blocks.There have been various researches carried out to overcome the limitation of fractal encoding and to speed up the encoder.The neighborhood search strategy used in spatial domain reduces the encoding time from linear time to logarithmic time.The proposed algorithm used k-nearest neighbor search to find the similar edge shaped range and domain blocks to be mapped on the basis of DCT lowest coefficients in horizontal and vertical directions and then using similarity measure; the virtual codebook was prepared to encode the image and then decoded the image using averaging of pixels of selected domains. The proposed approach explained in this book is compared with the existing method and this work gave high PSNR value, high compression ratio and reduced MSE computations with little decay in image quality which is acceptable.

About the Author

Indu Aggarwal has completed her M.Tech in Computer Science and Engineering from Amity University, Noida in 2015.She completed her research work in the area of Image Processing and presented various research papers in International Conferences. Her interest and passion of research encouraged her to write and to help people working in this area.