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Increasing the quality of reconstructed image through hybrid compression technique

Publication Type : Conference Proceedings

Publisher : International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)

Source : 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) (2017)

Url : https://ieeexplore.ieee.org/document/8389796

Keywords : block based DCT method, Data compression, DCT, Discrete cosine transforms, Discrete wavelet transforms, DWT, hybrid compression technique, Image coding, image compression algorithm, Image reconstruction, PCA, PCA technique, Principal component analysis, PSNR value, PSNRfinalll, Quality metrics, Reconstructed image, Set Partitioning in Hierarchical Trees compression technique, Signal to noise ratio, SPIHT, SPIHT compression method, Trees (mathematics)

Campus : Coimbatore

School : School of Engineering

Center : Electronics Communication and Instrumentation Forum (ECIF)

Department : Computer Science

Year : 2017

Abstract : A novel image compression algorithm based on the combination of three different techniques is presented. First, the image is compressed using PCA and then DCT is applied to the reconstructed image acquired from PCA technique. The reconstructed image from the block based DCT method is further compressed through the DWT based Set Partitioning In Hierarchical Trees (SPIHT) compression technique. At last, output reconstructed image will be evaluated with variety of quality metrics. The proposed novel technique is evaluated with the various quality metrics namely PSNR, SC, SNR. The PSNR value of the proposed technique is high, when compared with other existing techniques. The experiment reveals that the proposed compression method improves the quality of the reconstructed image.

Cite this Research Publication : S. D. Suganya, M. R. Reddy, and Madhusudana Rao Nalluri, “Increasing the quality of reconstructed image through hybrid compression technique”, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). 2017.

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