Abstract: Image compression is nothing but reducing the size of data required to represent an image. In the few recent years there is tremendous growth of data intensive and multimedia based applications, efficient image compression solutions are becoming critical. The main objective of Image Compression is to reduce redundancy of the data and improve the efficiency. The main techniques used are Fourier Analysis, Discrete Cosine Transform vector quantization method, sub-band coding method. The drawbacks in the above methods are, they cannot be used for real time systems. In order to overcome these problems, the Wavelet Transform method has been introduced. The signal processing after encryption that is in cryptosystem is relatively somewhat new topic. The data size to store available information require large memory, so here we are proposing a method called multilevel discrete wavelet transform(DWT) in encrypted domain. We are suggesting a frame work for carry out DWT and its inverse DWT in the encrypted domain. With this proposed framework we carry out multilevel DWT and inverse DWT in Homomorphic encrypted domain.

Keywords: Data Processing, Discrete Wavelet Transform (DWT), Inverse Discrete Wavelet Transform (IDWT), Encryption, Decomposition, DFT, FFT.