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A Novel Approach of Conventional Image Compression on Color Images and Transform Based Technique Using Discrete Cosine Transform




Lossy Compression, DCT, Redundancy, Storage Space, PSNR, MSE


Image compression is a most popular application of data compression on digital images. This compression is reducing the size in bytes of an image without corrupting the quality of the image. The minimization in file size allows more images to be stored in a given amount of disk or memory space. There are numerous different ways are existing for image compression. This paper concerned with the lossy compression techniques implemented for RGB Images, where data loss cannot affect the image quality and the clarity also will not be decreased with presenting the additional procedure for compressing methods. This compression technique is very popular. DCT Image Compression is very easy one for Greyscale images, while compressing the Colour image it is hard to implement. However, this RGB image compression has been implemented successfully. After compression the file size is reduced more and image quality is nearly the same. This analysis of compression techniques addresses the problem of minimizing the amount of data required to represent a digital image. It is also used for eliminating the redundancy that is avoiding the duplicate data. It also reduces the storage space to load an image. The main objectives of this paper are reducing the image storage space without corrupting the visual quality, Easy maintenance and providing security. The proposed Discrete Cosign Transform techniques efficiently work with RGB image which is compressed up to 90%, 80% 70%, 60%, 40% and 20% and optimum results are obtained. The analysis of obtained results has been carried out with the help of MSE (mean square error) and PSNR (peak signal to noise ratio). This compression method is entirely developed by using only basic MATLAB functions.

Other Details

Paper ID: IJSRDV3I70390
Published in: Volume : 3, Issue : 7
Publication Date: 01/10/2015
Page(s): 641-645

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