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Enhanced Image Compression Using Fractals and Principle Component Analysis

Publication Type : Conference Proceedings

Publisher : IEEE

Url : https://doi.org/10.1109/IHCSP56702.2023.10127168

Keywords : Technological innovation; Image coding; Termination of employment; Signal processing; Fractals; Real-time systems; Discrete cosine transforms; Ratio of compression; fractal; DCT; PCA; image compression

Campus : Faridabad

School : School of Artificial Intelligence

Year : 2023

Abstract : Fractal image compression is a lossy approach that makes efficient use of the picture's inherent redundancy using affine transformations. It has been discovered that the traditional method of searching for domain blocks in fractal images requires a considerable amount of encoding time. As a result, in order to raise the speed-up ratio, a hybrid architecture that combines fractals and the discrete cosine transform (DCT) with PCA has been developed in this study. The proposed hybrid design cuts down on the amount of time needed by employing a relatively small number of components, and it offers compression ratios and quality levels that are satisfactory.

Cite this Research Publication : Manish Tiwari, Vijayshri Chaurasia, Ebtasam Ahmad Siddiqui, Vivek Patel, Ana Kumar, Mamta Patankar, Enhanced Image Compression Using Fractals and Principle Component Analysis, [source], IEEE, 2023, https://doi.org/10.1109/IHCSP56702.2023.10127168

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