Mathematics Department, Aston University B4 7ET, Birmingham, United Kingdom.
Aurelien Inacio, ENSIIE, Paris, France.
PLoS One. 2023 Jan 26;18(1):e0279917. doi: 10.1371/journal.pone.0279917. eCollection 2023.
Transformations for enhancing sparsity in the approximation of color images by 2D atomic decomposition are discussed. The sparsity is firstly considered with respect to the most significant coefficients in the wavelet decomposition of the color image. The discrete cosine transform is singled out as an effective 3 point transformation for this purpose. The enhanced feature is further exploited by approximating the transformed arrays using an effective greedy strategy with a separable highly redundant dictionary. The relevance of the achieved sparsity is illustrated by a simple encoding procedure. On typical test images the compression at high quality recovery is shown to significantly improve upon JPEG and WebP formats.
讨论了通过二维原子分解来增强彩色图像逼近稀疏性的变换。首先考虑了彩色图像小波分解中最重要系数的稀疏性。离散余弦变换被选为实现这一目标的有效 3 点变换。通过使用有效的可分离高度冗余字典，对变换后的数组进行近似，进一步利用增强的特征。通过一个简单的编码过程说明了所获得的稀疏性的相关性。在典型的测试图像上，高质量恢复的压缩效果明显优于 JPEG 和 WebP 格式。
