This paper entails the study and analysis of various image compression techniques. Compression plays an important role in today’s world for efficient transmission and storage of data. Different techniques for digital image compression have been reviewed and presented that include Huffman Coding, Lemphel-Ziv-Welch (LZW) Coding, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT). Image compression may be lossy or lossless. Lossless Compression is preferred for archival purposes and often for medical imaging, technical drawings, etc. Lossy compression are especially suited for natural images such as photographs or where low bit rates are used. Lossless Compression techniques include huffman coding and Lemphel-Ziv-Welch (LZW). Lossy Compression techniques include Discrete Cosine Transform (DCT), Discrete Wavelet transform (DWT). Finally a performance comparison is made between these techniques based on different parameters like Peak Signal to Noise Ratio (PSNR), Compression ratio (CR), Root Mean Square Error (RMSE), etc.

Keywords : Compression ratio, Discrete Cosine Transform, Discrete Wavelet Transform, Huffman Coding, Lemphel-Ziv- Welch Coding, Peak Signal to Noise Ratio, Root Mean Square Error.