Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan.
Center for Cyber-physical System Innovation, National Taiwan University of Science and Technology, Taipei 10607, Taiwan.
Sensors (Basel). 2019 Mar 9;19(5):1214. doi: 10.3390/s19051214.
The JPEG-XR encoding process utilizes two types of transform operations: Photo Overlap Transform (POT) and Photo Core Transform (PCT). Using the Device Porting Kit (DPK) provided by Microsoft, we performed encoding and decoding processes on JPEG XR images. It was discovered that when the quantization parameter is >1-lossy compression conditions, the resulting image displays chequerboard block artefacts, border artefacts and corner artefacts. These artefacts are due to the nonlinearity of transforms used by JPEG-XR. Typically, it is not so visible; however, it can cause problems while copying and scanning applications, as it shows nonlinear transforms when the source and the target of the image have different configurations. Hence, it is important for document image processing pipelines to take such artefacts into account. Additionally, these artefacts are most problematic for high-quality settings and appear more visible at high compression ratios. In this paper, we analyse the cause of the above artefacts. It was found that the main problem lies in the step of POT and quantization. To solve this problem, the use of a "uniform matrix" is proposed. After POT (encoding) and before inverse POT (decoding), an extra step is added to multiply this uniform matrix. Results suggest that it is an easy and effective way to decrease chequerboard, border and corner artefacts, thereby improving the image quality of lossy encoding JPEG XR than the original DPK program with no increased calculation complexity or file size.
JPEG-XR 编码过程使用两种变换操作:照片重叠变换 (POT) 和照片核心变换 (PCT)。我们使用微软提供的设备移植工具包 (DPK) 对 JPEG XR 图像进行编码和解码处理。结果发现,当量化参数 >1(有损压缩条件)时,生成的图像会显示棋盘块状伪影、边界伪影和角部伪影。这些伪影是由于 JPEG-XR 使用的变换是非线性的。通常情况下,这些伪影并不那么明显;但是,在复制和扫描应用程序时,可能会出现问题,因为当图像的源和目标具有不同的配置时,它会显示非线性变换。因此,对于文档图像处理管道来说,考虑到这些伪影非常重要。此外,这些伪影在高质量设置下最成问题,在高压缩比下显得更加明显。在本文中,我们分析了上述伪影的原因。结果发现,主要问题在于 POT 和量化步骤。为了解决这个问题,提出了使用“均匀矩阵”的方法。在 POT(编码)之后和逆 POT(解码)之前,添加一个额外的步骤来乘以这个均匀矩阵。结果表明,这是一种简单有效的方法,可以减少棋盘状、边界和角部伪影,从而提高有损编码 JPEG XR 的图像质量,优于原始 DPK 程序,而不会增加计算复杂度或文件大小。