First, the input image is loaded and then the image is filtered. Gaussian filter is used for filtering process because it is used for removing the noise and smoothening the image. In the data hiding technique , secret data can be hide and retrieved. In the compression technique , we will obtain image blocks by using wavelet filter and then the image is compressed by SMVQ. Finally, it achieves higher decompression quality than the SMVQ method. Then we plot the graph for the relationship between data hiding and threshold .The performance is calculated for CR , PSNR and SSIM.Vector quantization is also utilized for some complex blocksto control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values. In the data hiding technique , secret data can be hide and retrieved. Data-hiding is used for converting communication of secret data. Secret datas are embedded in the image and then successfully we can extract the secret datas in the data hiding technique. It is used for protection and authentication of images. The image compression is mainly depend on SMVQ mechanism. The image blocks are labelled using wavelet filtering process. Side match vector quantization (SMVQ) is an image compression scheme that reduces the redundancy of a digital image. SMVQ is used for recovering the blocks and for transmitting the confidential information.