SSIM based image quality assessment for lossy image compression

With the wide use of computers and consequently need for large scale storage and transmission of data efficient ways of storing of data have become necessary. With the growth of technology and entrance into the Digital Age the world has found itself amid a vast amount of information. Dealing with such enormous information can often present difficulties. Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages.JPEG and JPEG 2000 are two important techniques used for image compression. Both are Lossy compression scheme that are often used to compress information such as digital images. Image processing is the latest field of research now days. Image Compression is the field of Image processing which includes the compression of Images and is chosen for the thesis work. JPEG 2000 image compression standard makes use of DWT (Discrete Wavelet Transform). DWT can be used to reduce the image size without losing much of the resolutions computed and values less than a pre-specified threshold are discarded. Thus it reduces the amount of memory required to represent given image. Recently discrete wavelet transform has emerged as popular techniques for image compression. The wavelet transform is one of the major processing components of image compression. For image compression, it is desirable that the selection of transform should be responsible for reducing the size of resultant data set as compared to source data set. This thesis is focused on parameter related to image such as compression ratio, PSNR, MSE, Global thresholding and SSIM.