An efficient image compressor for charge coupled devices camera.

Area of Science:

• Image compression
• Remote sensing technology
• Signal processing

Background:

• Discrete Wavelet Transform (DWT) is state-of-the-art for Charge Coupled Devices (CCD) cameras.
• DWT on CCD images yields many high-amplitude, high-frequency coefficients, hindering subsequent coding.
• Complex textures and contours in CCD images pose challenges for traditional compression.

Purpose of the Study:

• To propose a low-complexity posttransform coupled with compressed sensing (PT-CS) for remote sensing image compression.
• To improve compression efficiency for CCD camera images.
• To reduce the implementation complexity compared to existing methods like JPEG2000.

Main Methods:

• Applied Discrete Wavelet Transform (DWT) to remote sensing images.
• Introduced a posttransform using DCT or Hadamard bases on DWT coefficients.
• Selected the optimal posttransform via an l p -norm-based approach.
• Utilized compressed sensing (CS) principles for sparse representation and resampling.

Main Results:

• The PT-CS approach significantly outperforms the CCSDS-IDC coder.
• Performance is comparable to JPEG2000 at low bit rates.
• Achieved lower implementation complexity than JPEG2000.

Conclusions:

• The proposed PT-CS method offers an effective and efficient compression solution for remote sensing images.
• This approach balances high compression performance with reduced computational cost.
• PT-CS is a viable alternative for on-board CCD camera image compression.