Comparative Analysis: Pca and Jpeg

This paper mainly address the image compression by using Principal component analysis (PCA) and JPEG. Image compression is the method of converting data file into smaller compact files for efficiency of storage and transmission. The main objective of compression of image is to reduce redundancy of bits in the image in order to store and transmit data in an effective way. Image compression techniques deal with the problem of reduction in size of the file which results in efficient storage of image and bandwidth to transmit it. Image Compression helps in storage of more information in a given memory space.PCA is mathematical tool which is used for reducing the dimensionality of data .PCA extracts major variation in the data sets while removing other insignificant components. In this paper PCA is applied for image compression. Since PCA compression is lossy the compressed image is generally degraded as compared to original image. Also PCA is compared with most commonly used image compression technique which is JPEG.JPEG is also a lossy image compression technique which start by separating the image into 8*8 pixel groups and applying DCT transform individual 8*8 pixel groups .In this paper PCA and JPEG compression are applied to the image and various parameter like PSNR and MSE is calculated for both of the compression technique. The Mean Square Error (MSE) and the Peak Signal to Noise Ratio (PSNR) are the two error parameter used to compare image compression quality