One of the application in satellite communication is to capture and transmit high quality and hyper-spectral images back to the ground station. These images require very high bandwidth, more transmission time and large storage memory. Moreover, the link used for communication is susceptible to various noises. Hence, need for image compression with high compression ratio and channel encoding technique with minimum distortion becomes imperative. In this paper, we have proposed a quality constrained compression algorithm for space images based on novel Sub-band Replacement-Discrete Wavelet Transform (SR-DWT) technique. It has spatial-frequency decomposition property that provides quality assessment for captured images. Also, a Low-Density Parity Check (LDPC) encoder for channel coding is proposed to minimize the effect of noise over the transmission channel. The various image quality parameters viz. Peak Signal to Noise Ratio (PSNR), Processing Time, Compression ratio etc are evaluated and plotted against bits per pixel (bpp).