A Simplified Fractal Texture Analysis Approach using Quadtree Decomposition with Huffman Coding Technique 2021 September

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dc.contributor.authorJacob, Rani
dc.date.accessioned2025-07-24T16:47:35Z
dc.date.available2025-07-24T16:47:35Z
dc.date.issued2021
dc.description.abstractFractal compression is compression of the lossy type, which is applied for natural textured images. A fractal image compression technique based on the Quadtree algorithm and Huffman coding is proposed in this work. Agonizingly, the term "fractal compression" refers to an image compression technique that uses the fractal geometry of the image data stream to achieve lossy compression. Realistic images and textures are created with the help of this tool. It is based on the fact that parts of an image are frequently similar to other parts of the same image, which allows for faster processing. The most widely used partitioning mechanism is image partitioning in a tree structure. In this emerging world of image processing, quad tree partitioning is a one-of-a-kind technique that divides an image into a set of homogeneous regions. Huffman coding is a type of data compression that is lossless. The Huffman encoding algorithm is introduced through this technique, which creates an alphabetic list of all of the alphabet symbols, which is then arranged in descending order of their likelihood of occurring. The peak signal-to-noise ratio is quite improved by employing the proposed technique, and the encoding time is reduced.
dc.identifier.issn2582-0974
dc.identifier.urihttps://ds.dmiseu.org/handle/123456789/94
dc.language.isoen
dc.publisherMiddle East Journal of Applied Science & Technology
dc.subjectImage processing
dc.subjectCompression
dc.subjectQuadtree
dc.subjectHuffman coding.
dc.titleA Simplified Fractal Texture Analysis Approach using Quadtree Decomposition with Huffman Coding Technique 2021 September
dc.typeArticle

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