提高离散余弦变换图像压缩的效率和灵敏度及与离散小波变换的比较

2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) Pub Date : 2022-10-10 DOI:10.1109/ICTACS56270.2022.9987984

P. Dinesh, G. Uganya

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引用次数: 1

摘要

本文旨在利用离散余弦变换对彩色图像进行压缩，并与离散小波变换(DWT)进行效率和灵敏度的比较。实现了新颖的DCT和DWT算法，在不损失图像质量的情况下压缩图像。第1组20个样本使用DWT，第2组20个样本使用Novel DCT。这两组可以在采集40个样本的情况下进行。对这些算法进行了实现，以评估压缩图像的效率和灵敏度。仿真结果表明，该算法的图像压缩比为23:1，效率为96%，灵敏度为98%。DWT算法的图像压缩比为21:1，效率为94%，灵敏度为93%。所得显著性值为0.02，小于0.05。该算法比DWT算法具有更高的效率和灵敏度。

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Enhancing the Efficiency and Sensitivity in Discrete Cosine Transform based Image Compression and Comparing with Discrete Wavelet Transform

This work aims to compress the color images using Novel DC transform (Discrete Cosine Transform) and compare the efficiency and sensitivity with Discrete Wavelet Transform (DWT). Novel DCT and DWT algorithms were implemented to compress the image without losing quality. Group 1 with 20 samples using DWT and group 2 with 20 pieces using Novel DCT. These two groups can be performed with the help of collecting 40 samples. These algorithms were implemented to evaluate the efficiency and sensitivity of the compressed images. From the simulation result, the proposed algorithm achieves the image compression ratio of 23:1 with 96% efficiency and 98% sensitivity. The DWT algorithm achieves an image compression ratio of 21:1 with 94% of efficiency and 93% of sensitivity. The significance value obtained was 0.02, which is less than 0.05. The novel DCT algorithm has significantly better efficiency and sensitivity than the DWT algorithm.

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2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)

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