Name
Abstract | ||
|---|---|---|
Some image and video processing algorithms can have the unintended consequence of introducing blocking artifacts into the processed imagery. Measuring blockiness plays an important role in many applications. This paper presents a reference-free blockiness measurement method. For a given image, the absolute difference between horizontally adjacent pixels is computed, normalized, and averaged along each column. A one-dimensional discrete Fourier transform is thereafter employed and a vertical blockiness measure is derived. A horizontal blockiness measure is computed similarly. Finally, a blockiness measure for the given image is formulated by pooling those two directional blockiness measures. The proposed method can accurately assess the blockiness without any a priori knowledge of the block origin and block size; therefore it is a blind measure. Experimental results show the effectiveness of the proposed method. The robustness of the proposed method is also justified. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15702-8_11 | PCM (1) |
Keywords | Field | DocType |
blockiness measure,blind reference-free blockiness measure,directional blockiness measure,block size,block origin,vertical blockiness measure,blind measure,reference-free blockiness measurement method,absolute difference,horizontal blockiness measure,discrete fourier transform,a priori knowledge,video processing | Block size,Computer vision,Video processing,Normalization (statistics),Pattern recognition,Computer science,A priori and a posteriori,Robustness (computer science),Pixel,Artificial intelligence,Discrete Fourier transform,Absolute difference | Conference |
Volume | ISSN | ISBN |
6297 | 0302-9743 | 3-642-15701-7 |
Citations | PageRank | References |
16 | 0.67 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunhua Chen | 1 | 16 | 0.67 |
| Jeffrey A Bloom | 2 | 377 | 52.32 |