The most recent (early 1990s) development in error correction is Turbo coding, a

scheme that combines two or more relatively simple convolutional codes and an

interleaver to produce a code that can perform to within a fraction of a decibel to the Shannon’s limit. A Turbo Code can be thought as a refinement of the concatenated encoding structure plus an iterative algorithm for decoding the associated code sequence. The codes are constructed by using two or more component codes on different interleaved versions of the same information sequence. Turbo codes can be implement in different applications like image, video, mobile communication and satellite communication etc. We are planning to implement the Turbo Code with the Image. With the help of adding few turbo codes using iteration process with the image data we can get the control over the error bit present in the past image data. And at the end using proper number of iterations, compression of the image will get and after getting compressed image, in this image error bit rate will be less. We will implement first this turbo codes in software (MATLAB). The key innovation of turbo codes is an interlever. This permutes the original k information bits before input to the second encoder. The permutation allows that input sequences for which one encoder produces low weight codeword will usually cause the other encoder to produce high weight code words. Thus even though the constituent codes are individually weak, the combination is surprisingly powerful.With these concepts of turbo code, implementation of turbo codes to transmit image and approach to improving error control performance through joint channel and source decoding (JCSD). These systems are based on a modification of extrinsic information passed between the constituent maximum a posteriori probability (MAP) decoders in a turbo decoder.