Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/14789
Title: Image compression using fractals for color and textured images
Researcher: Sankaragomathi.B.
Guide(s): Ganesan.L
Keywords: Image compression, fractals, color, textured images, Multiple Reduction Copying Machine
Upload Date: 7-Jan-2014
University: Manonmaniam Sundaranar University
Completed Date: December 2008
Abstract: This Research work particularly deals with fractal image compression with an idea to minimize the computational requirements to achieve enhanced reproduction of image quality. Problems such as use of fractal geometry for image compression, extension of this concept for color image compression, encoding of video sequences in compression, application of the concept of compression for remote-sensed images, use of wavelets in fractal compression algorithm for enhanced performance, and extension of wavelet-based fractal concept for compression of textured images have been discussed in this study. newlineThe concept of wavelet is combined with this to enhance the performance. Fractal image compression is desirable because of its resolution independence, faster decoding and competitive rate distortion curves. However, the main drawbacks in the Fractal Image compression method, such as longer computation time for encoding and heavy computation for full and exhaustive search, have been alleviated using Partitioned Iterated Function Systems in this study. This method is also used to compress the color and textured images. RGB components in the color images are encoded independently. Here, only the partial distance is calculated while comparing the range with domain blocks. Domain blocks with minimum distance are selected. Thus a high compression ratio can be achieved. newlineFidelity and efficiency of the restored images by fractal techniques are better compared with the previous image compression methods. It has a high compression rate when compared with JPEG and wavelet. The results cover the comparisons of original and reconstructed images, fidelity evaluation and analysis of compression rates on different land covers, different resolutions and discussion on the efficiency of the algorithms. Heavy reduction in encoding-decoding time is achieved by combining the wavelet with fractal. newline
Pagination: xv, 165p.
URI: http://hdl.handle.net/10603/14789
Appears in Departments:Centre for Information Technology and Engineering

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01_titiles.pdfAttached File48.22 kBAdobe PDFView/Open
02_certificate.pdf16.22 kBAdobe PDFView/Open
03_declaration.pdf12.86 kBAdobe PDFView/Open
04_acknowledgement.pdf18.69 kBAdobe PDFView/Open
05_contents.pdf26.15 kBAdobe PDFView/Open
06_list of tables.pdf20.23 kBAdobe PDFView/Open
07_chapter 1.pdf234.77 kBAdobe PDFView/Open
08_chapter 2.pdf2.23 MBAdobe PDFView/Open
09_chapter 3.pdf233.86 kBAdobe PDFView/Open
10_chapter 4.pdf163.44 kBAdobe PDFView/Open
11_chapter 5.pdf383.09 kBAdobe PDFView/Open
12_chapter 6.pdf93.86 kBAdobe PDFView/Open
13_chapter 7.pdf50.87 kBAdobe PDFView/Open
14_abbreviations.pdf20.18 kBAdobe PDFView/Open
15_references.pdf86.37 kBAdobe PDFView/Open


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