Removal Of Blocking Artifacts From JPEG-Compressed Images Using An Adaptive Filtering Algorithm

The aim of this research was to develop an algorithm that will produce a considerable improvement in the quality of JPEG images, by removing blocking and ringing artifacts, irrespective of the level of compression present in the image. We review multiple published related works, and finally present a computationally efficient algorithm for reducing the blocky and Gibbs oscillation artifacts commonly present in JPEG compressed images. The algorithm alpha-blends a smoothed version of the image with the original image; however, the blending is controlled by a limit factor that considers the amount of compression present and any local edge information derived from the application of a Prewitt filter. In addition, the actual value of the blending coefficient (α) is derived from the local Mean Structural Similarity Index Measure (MSSIM) which is also adjusted by a factor that also considers the amount of compression present. We also present our results as well as the results for a variety of other papers whose authors used other post compression filtering methods

Removal Of Blocking Artifacts From JPEG-Compressed Images Using Neural Network

The goal of this research was to develop a neural network that will produce considerable improvement in the quality of JPEG compressed images, irrespective of compression level present in the images. In order to develop a computationally efficient algorithm for reducing blocky and Gibbs oscillation artifacts from JPEG compressed images, we integrated artificial intelligence to remove blocky and Gibbs oscillation artifacts. In this approach, alpha blend filter [7] was used to post process JPEG compressed images to reduce noise and artifacts without losing image details. Here alpha blending was controlled by a limit factor that considers the amount of compression present, and any local information derived from Prewitt filter application in the input JPEG image. The outcome of modified alpha blend was improved by a trained neural network and compared with various other published works [7][9][11][14][20][23][30][32][33][35][37] where authors used post compression filtering methods

Coding artifact reduction using non-reference block grid visibility measure

In this work a new method is proposed for coding artifact reduction of MPEG compressed video sequences. The method makes use of a simple cost-effective technique that allows the block grid position and its visibility to be determined without the need for access to the coding parameters. This information, combined with the results of local spatial analysis of luminance and chrominance components of a decoded image, is used to effectively suppress coding artifacts while preserving the sharpness of object edges. Results of our experiments confirm the high efficiency of the proposed approach. 1