An adaptive coding pass scanning algorithm for optimal rate control in biomedical images

Area of Science:

• Biomedical imaging
• Image compression algorithms
• Telemedicine technology

Background:

• High-efficiency and high-quality biomedical image compression is crucial for telemedicine.
• Existing compression methods may not be optimal for rate control and resource utilization.

Purpose of the Study:

• To present an adaptive coding pass scanning (ACPS) algorithm for optimal rate control in biomedical image compression.
• To improve computational efficiency and memory space utilization compared to benchmark algorithms.

Main Methods:

• Developed an adaptive coding pass scanning (ACPS) algorithm.
• Implemented ACPS to identify and prioritize significant image portions, discarding insignificant data early.
• Replaced the postcompression rate distortion (PCRD) benchmark algorithm with ACPS for comparative analysis.

Main Results:

• ACPS effectively identifies significant image regions, discarding less important data early.
• The ACPS algorithm demonstrates superior performance over PCRD in rate-distortion curves.
• ACPS significantly reduces computation time compared to PCRD.

Conclusions:

• ACPS offers a more efficient and effective approach to biomedical image compression.
• The algorithm's ability to optimize rate control makes it highly suitable for telemedicine.
• ACPS provides a valuable alternative to existing methods, enhancing resource management.