Recce imagery compression options

ABSTRACT The errors introduced into reconstructed RECCE imagery by ATARS DPCM compression are compared to those introducedby the more modem DCT-based JPEG compression algorithm. For storage applications in which uncompressed sensor data isavailable JPEG provides better mean-square-error performance while also providing more flexibility in the selection ofcompressed data rates. When ATARS DPCM compression has already been performed, lossless encoding techniques may beapplied to the DPCM deltas to achieve further compression without introducing additional errors. The abilities of severallossless compression algorithms including Huffman, Lempel-Ziv, Lempel-Ziv-Welch, and Rice encoding to provide thisadditional compression of ATARS DPCM deltas are compared. It is shown that the amount of noise in the original imagerysignificantly affects these comparisons.Keywords: RECCE, JPEG compression, reconnaissance imagery, recompressing ATARS DPCM, noise effects I. INTRODUCTION The Advanced Tactical Air Reconnaissance System (ATARS) differential pulse-code modulation (DPCM) algorithm forcompressing RECCE imagery was introduced in the late 1980s. Since then advances in algorithms based on the discretecosine transform (DCT) combined with advances in VLSI technology have made better performing but more complexalgorithms practical for RECCE applications. The Joint Photographic Experts Group developed the DCT-based JPEGstandard [PM93] for compressing still imagery. The JPEG algorithm is directly applicable to frames of non-overlappingimagery such as those produced by pushbroom sensors. For forward-looking sensors which produce sequences of overlappingimagery JPEG could be used but would not take advantage of the redundancy contained in the frame-to-frame overlap. Forforward-looking sensors more efficient compression is achieved using motion estimation and compensation such asincorporated in the Motion Picture Experts Group (MPEG) standards. This paper deals only with intraframe compressionapplicable to non-overlapping sensor imagery.ATARS DPCM is designed to achieve a nominal 2: 1 compression ratio for original 8-bit sensor data by encoding using 4-bitdeltas. Lossless coding techniques may be applied to these delta values to achieve additional compression. However, theamount of compression achieved will vary widely depending on the imagery and be totally uncontrollable by the user. TheJPEG compression algorithm provides a means for achieving better performance when compressing direct sensor data at thenominal 2: 1 compression ratio of ATARS DPCM while allowing for the flexibility of selecting higher compression ratios. Forlow noise imagery JPEG can achieve 8: 1 compression while still maintaining high quality reconstructed results.This paper will compare the reconstructed image errors introduced by ATARS DPCM to those introduced by JPEG. InSection II the model used herein for ATARS DPCM simulations will be described. Lossless algorithms considered ascandidates for recompressing the 4-bit ATARS DPCM deltas are presented in Section III. Quantitative comparisons are madeof the compression ratios achieved by these lossless algorithms. Section IV provides a brief description of the JPEGalgorithm. Section V compares the reconstructed image quality achieved by ATARS DPCM to that achieved by JPEG. Thispaper concludes with Section VI.232