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Improvement in DPCM image compression technique
Author(s): A. Kumar, R. Kumaran, S. Paul, R.M. Parmar
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Type: ConferencePaper
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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 becomes mandatory. DPCM is one prediction based image compression technique (10:7) used in Resourcesat-2 mission. Based on received data from this mission, some artifacts are reported at high contrast targets as expected. Hence, an effort is made to analyze and improve the existing DPCM technique with minimum hardware modification by increasing the quantizer dynamic range and maintaining similar radiometric performance at low contrast locations. Newly developed technique provides RMSE of 16 counts compared to 41 counts with very high contrast image. Ringing artifacts are reduced to 7.6% compared to 38.2% with existing technique. Developed technique has low complexity and can be implemented in a low end FPGA without any external memory.

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Low complex ADPCM image compression technique
Author(s): A. Kumar, R. Kumaran, S. Paul, R.M. Parmar
Source:
Type: ConferencePaper
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Future high resolution optical instruments for space remote sensing will lead to higher data volumes. Hence, on-board image compression becomes mandatory considering constraints in data rate. MLG (MultiLinear-Gain) compression (12:10) technique has been used in AWiFS payload of Resourcesat-2 mission. The main advantage of MLG is its improved SNR at low reflectance values and low on-board hardware resources. However SNR degrades at high reflectance values. Hence, a study is carried out to improve SNR performance in entire dynamic range. Adaptive Differential Pulse Code Modulation (ADPCM) is one prediction based image compression technique, which has been used by other space agencies with their own proprietary algorithm. Hence a custom ADPCM technique with two quantizers is developed while maintaining similar 12:10 interface. Developed technique provides improved SNR throughout full dynamic range and recovers >99.5% pixel data losslessly. Root-Mean Square Error (RMSE) performance is also improved from 1.5 to 17 times depending on image contrast. Developed technique is low complex and can be implemented in low end FPGA without any additional memory.

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