Abstract
In recent years, domain image processing plays a most significant role in realtime applications. Due to reserved bandwidth and capacity, images are needed to be compressed, enhance, and noise-free to reduce the storage space as well as the transmission time. Compression overcomes the problem such as insufficient bandwidth of network and storage of memory device. Nowadays, many techniques are used to compress an image with a good quality. In this paper, I briefly discuss the concept of image compression and review the techniques which are used in loss image compression. This technique losses some data by using transform codes. Two codes are used to compress an image such as wavelet and fractal. The techniques scalar and vector quantization are used to quantize an input and partition into sub-images. I briefly discussed about the 2D-Discrete wavelet transform codes with examples which were done by Mat lab software.
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