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Vol. 8, Issue 3 (2019)

Image compression using discrete cosine transform and discrete wavelet transform

Pragati Upadhyay and Archana Singh
The large amount of digital data being created, store and transferred over the internet calls for optimum usage of available data storage capabilities. Images forms the bulk of the data and thus study and application of image compression becomes inevitable. In this research work, a thorough investigation into the image compression paradigm has been presented. The two commonly used techniques of image compression viz. Discrete cosine based Image compression and Discrete Wavelet based Image Compression techniques have been presented here. The techniques have been discussed by comparing the performance of the algorithm on a number of images. The images used are standard images of varying sizes. The techniques have been applied successfully and the results of compression using both the techniques have been compiled. The comparison shows as given in the results chapter that for the same input image the compression in DCT technique is more than the DWT technique. However, the quality of the image decreases. There always lies a tradeoff between the compression ratio and perceptual quality of the image obtained and it largely depends on the usage to decide the priority of which method to choose over the other. If the focus and usage is entirely on compression and image quality is a less important factor, then the preferred method should be DCT as described in this thesis. However, if the quality of image is also to be maintained while compressing into smaller disk size, then the DWT based compression technique must be employed.
Pages: 141-146  |  872 Views  151 Downloads

The Pharma Innovation Journal
How to cite this article:
Pragati Upadhyay, Archana Singh. Image compression using discrete cosine transform and discrete wavelet transform. Pharma Innovation 2019;8(3):141-146.

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