基于总变分JPEG2000核磁共振图像解码算法

Based on the total variational JPEG2000 nuclear magnetic resonance images decompression algorithm

针对低比特JPEG2000图像因压缩过程中产生的压缩痕迹问题,提出一种总变分JPEG2000解码算法。首先通过分析JPEG2000压缩的量化噪声近似地服从高斯分布,得到一个总变分ROF解码模型。其次利用原对偶算法求解所提出的ROF模型得到一个最优化解码迭代方案。最后对两幅核磁共振图像进行实验仿真,通过与高斯滤波、中值滤波方法在SNR值、视觉效果等方面进行比较,验证了本文方法去除压缩痕迹方面的有效性。

Focused on the defect that artifacts in low-bit JPEG2000 images because of rounding the data in the encoder,a total variation based JPEG2000 decompression algorithm was proposed.Firstly,by analyzing the quantization noise compressed by JPEG2000,it approximately follows the Gaussian distribution,so a total variation ROF decoding model was obtained;Secondly,the primal dual algorithm is used to solve the proposed ROF model to obtain an optimized decoding iteration scheme;Finally,the two nuclear magnetic resonance images are experimentally simulated,simulate results compared with the Gauss and median filters in terms of SNR value and visual effect.The experimental results demonstrate that the proposed method has the effectiveness of removing the artifacts of compression.