Zhu Yaohua, Liu Ya, Zhu Yanghang, Huang Mingsheng, Jiang Jingyu, Zhang Yong
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2025 Apr 15;25(8):2491. doi: 10.3390/s25082491.
Infrared line-scanning images have high redundancy and large file sizes. In JPEG2000 compression, the MQ arithmetic encoder's complexity slows down processing. Huffman coding can achieve O(1) complexity based on a code table, but its integer-bit encoding mechanism and ignorance of the continuity of symbol distribution result in suboptimal compression performance. In particular, when encoding sparse quantized wavelet coefficients that contain a large number of consecutive zeros, the inaccuracy of the one-bit shortest code accumulates, reducing compression efficiency. To address this, this paper proposes Huf-RLC, a Huffman-based method enhanced with Run-Length Coding. By leveraging zero-run continuity, Huf-RLC optimizes the shortest code encoding, reducing the average code length to below one bit in sparse distributions. Additionally, this paper proposes a wavelet coefficient probability model to avoid the complexity of calculating statistics for constructing Huffman code tables for different wavelet subbands. Furthermore, Differential Pulse Code Modulation (DPCM) is introduced to address the remaining spatial redundancy in the low-frequency wavelet subband. The experimental results indicate that the proposed method outperforms JPEG in terms of PSNR and SSIM, while maintaining minimal performance loss compared to JPEG2000. Particularly at low bitrates, the proposed method shows only a small gap with JPEG2000, while JPEG suffers from significant blocking artifacts. Additionally, the proposed method achieves compression speeds 3.155 times faster than JPEG2000 and 2.049 times faster than JPEG.
红外行扫描图像具有高冗余度和大文件尺寸。在JPEG2000压缩中，MQ算术编码器的复杂性会降低处理速度。哈夫曼编码基于码表可实现O(1)的复杂度，但其整数位编码机制以及对符号分布连续性的忽视导致压缩性能次优。特别是在对包含大量连续零的稀疏量化小波系数进行编码时，一位最短码的不准确性会累积，降低压缩效率。为解决这一问题，本文提出了Huf-RLC，一种基于哈夫曼并通过游程编码增强的方法。通过利用零游程连续性，Huf-RLC优化了最短码编码，在稀疏分布中将平均码长降低到一位以下。此外，本文提出了一种小波系数概率模型，以避免为不同小波子带构建哈夫曼码表时计算统计量的复杂性。此外，引入差分脉冲编码调制（DPCM）来解决低频小波子带中剩余的空间冗余。实验结果表明，所提出的方法在PSNR和SSIM方面优于JPEG，同时与JPEG2000相比保持最小的性能损失。特别是在低比特率下，所提出的方法与JPEG2000之间的差距很小，而JPEG则存在明显的块状伪影。此外，所提出的方法实现的压缩速度比JPEG2000快3.155倍，比JPEG快2.049倍。
