Reducing blocking artifacts in JPEG-compressed images using an adaptive neural network-based algorithm

Zhang, Yuhong; Salari, Ezzatollah; Zhang, Shuangteng

doi:10.1007/s00521-011-0740-1

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Figure 6(b) is a reconstructed image using the improved quantization approach, and the image distortion problem is solved by adding zero-mean noise processing which has greatly improved the image reconstruction effect. Figure 6(c) uses a neural network-based deblocking method to reconstruct images [31]. Figure 6(d) uses a novel frame-wise filtering method to reconstruct images [32].…”

Section: Comparison Analysismentioning

confidence: 99%

Improving the Quality of Left-Behind Children’s Participation in Sports through Wireless Network Monitoring

Zhao

2021

Mobile Information Systems

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Urbanization is the process that people shift from rural to urban areas, which has led to large numbers of left-behind children in China. The left-behind children stay in rural regions of China while their parents work in urban areas. The left-behind children have few opportunities to participate in sports due to the lacking of concern, and it is not of high quality even though they participate in sports. Therefore, it is necessary to improve the quality of left-behind children's sports participation through wireless network monitoring. Wireless network monitoring transmits high-definition (HD) video streaming in real time to facilitate feedback timely. This paper studies the two-dimensional (2D) integer discrete cosine transform (DCT) and analyzes the reason for image distortion, then an improved DCT coefficient quantization approach is proposed for long-distance real-time transmission of HD video streaming, and a noise processing with a zero-mean noise processing is added in optimized approach to solve the image distortion problem. The experimental results show that the proposed improved approach has a good performance in reducing the blocking artifacts, and within the image reconstruction, the proposed approach improves the subjective video quality.

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Section: Comparison Analysismentioning

confidence: 99%