In high radiometric resolution electro optical image payloads of remote sensing satellites, photon noise dominates SNR performance. Photon noise is input signal dependent and difficult to filter. This paper proposes a photon noise filtering technique for Ocean Color Monitor (OCM) images. Existing filtering techniques are meant for object detection and handles images with poor SNR. As OCM SNR is on higher side, custom sigma filter based denoising technique is developed. Proposed technique first converts photon noise to signal independent Gaussian noise. For this variance stabilization, Anscombe transform is used. Simulations are carried on various images. Proposed technique provides 20- 50% reduction in overall as well count-wise RMSE. FFT analysis shows significant reduction in noise. Proposed technique is of low complexity.

ISRO's remote sensing continuity mission Resourcesat-II provided better radiometric performance as compared to Resourcesat-I. However, this improvement required implementation of onboard image compression techniques to maintain same transmission interface. In LISS-4 payload, prediction based DPCM technique with 10:7 compression ratio was implemented. Based on received data from this payload, some ringing artifacts were reported at high contrast targets, which degrade image quality significantly. However occurrences of such instances were very few. For future missions, efforts are made to develop an improved low complex image compression technique with better radiometry and lesser artifacts. Adaptive DPCM (ADPCM) technique provides better radiometric performance. This technique has been implemented onboard by other space agencies with their own proprietary algorithm. To maintain existing 10:7 compression ratio, novel ADPCM techniques with adaptive quantizers are developed. Developed ADPCM techniques are unique w.r.t. predictor and encoding. Developed techniques improve RMSE from 1.3 to 10 times depending on image contrast. Ringing artifacts are reduced to 1% from 38% with previous technique. Developed techniques are of low complexity and can be implemented in low end FPGA.

Future high resolution instrument planned by ISRO for space remote sensing will lead to higher data rates because of increase in resolution and dynamic range. Hence, image compression implementation becomes mandatory. Presently designed compression technique does not take account of imaging system noise like photon noise etc. This ignorance affects compression system performance. As a solution, this paper proposes MLG (Multi Linear Gain) operation prior to main compression system. With digital MLG operation, captured image can be optimally adjusted to systems noise. Proposed MLG operation improves compression ratio. Simulation results show 15-30% improvement in lossless compression ratio. However this improvement depends on MLG gains and corner points which can be driven by system SNR plot. MLG operation also helps in improving SNR at lower radiance input, when lossy JPEG2000 compression is used as main compression. Up to 1-6 dB SNR improvement is observed in simulations. Proposed MLG implementation is of very low complexity and planned to be used in future missions.