Blocking Artifacts In Images Research Articles

Using edge direction information for measuring blocking artifacts of images

Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifacts measurement consistent with subjective rating.

A locally adaptive algorithm for measuring blocking artifacts in images and videos

Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring image quality of a BDCT coded images or videos. It exhibits unique and useful features: (1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; (2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; (3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; (4) the quality measure is well defined in the range of 0–10. Experiments on various still images and videos show that the new quality measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.

A locally adaptive algorithm for measuring blocking artifacts in images and videos

Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring image quality of a BDCT coded images or videos. It exhibits unique and useful features: (1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; (2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; (3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; (4) the quality measure is well defined in the range of 0–10. Experiments on various still images and videos show that the new quality measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.

A de-blocking algorithm and a blockiness metric for highly compressed images

Blockiness is a typical artifact in reconstructed images that have been coded by a block-based discrete cosine transform (BDCT). In highly compressed images and video, the blocking artifacts are easily noticeable as the discontinuities between relatively homogeneous regions. Many current noniterative de-blocking algorithms attempt to remove the blocking artifacts by smoothing a few pixels around the block boundaries; however, the results are not satisfactory, especially at very low bit rates. We propose a de-blocking algorithm based on the number of connected blocks in a relatively homogeneous region, the magnitude of abrupt changes between neighboring blocks, and the quantization step size of DCT coefficients. Due to its adaptability, the proposed algorithm can smooth out the blocking artifacts while keeping the strong edges and texture areas untouched. Since this algorithm is noniterative and only identifies those block pairs that actually need de-blocking, its computation cost is low. In addition, we have developed a new metric to measure the blocking artifacts in images. Through analyzing the 2N-point (N is the block size) one-dimensional DCT coefficients of the two neighboring blocks with blocking artifacts, we show that all of the even DCT coefficients of the combined 2N points are zeros (except frequency k=0). The odd DCT coefficients are proportional to the pixel value difference between these two blocks with their magnitudes almost inversely proportional to frequency k. We selected the first DCT coefficient (frequency k=1) as an indicator for the strength of blocking artifacts in the reconstructed images. For the postprocessed images, we used a weighted summation of the squared first DCT coefficient to measure their blocking artifacts. Experimental results demonstrate that our proposed de-blocking algorithm produces better results than other methods, both visually and quantitatively, while the proposed blocking artifact metric is more consistent with subjective evaluation than the peak signal-to-noise ratio.