Image or video resources are often received in poor condition, mostly with noise or defects making the resources hard to read. We propose an effective algorithm based on digital image inpainting. The mechanism can be ...Image or video resources are often received in poor condition, mostly with noise or defects making the resources hard to read. We propose an effective algorithm based on digital image inpainting. The mechanism can be used in restoring images or video frames with very high noise or defect ratio (e.g., 90%). The algorithm is based on the concept of image subdivision and estimation of color variations. Noises inside blocks of different sizes are inpainted with different levels of surrounding information. The results showed that an almost unrecognizable image can be recovered with visually good result. The algorithm can be further extended for processing motion picture with high percentage of noise.展开更多
Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding w...Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding with edge alignment. This method uses blocks of size 4 × 4 and its basic idea is to find motion vector using the edge position in each video coding block. The method finds the motion vectors more accurately and faster than any known classical method that calculates all the possibilities. Our presented algorithm is compared with known classical algorithms using the evaluation function of the peak signal-to-noise ratio. For comparison of the methods we are using parameters such as time, CPU usage, and size of compressed data. The comparison is made on benchmark data in color format YUV. Results of our proposed method are comparable and in some cases better than results of standard classical algorithms.展开更多
文摘Image or video resources are often received in poor condition, mostly with noise or defects making the resources hard to read. We propose an effective algorithm based on digital image inpainting. The mechanism can be used in restoring images or video frames with very high noise or defect ratio (e.g., 90%). The algorithm is based on the concept of image subdivision and estimation of color variations. Noises inside blocks of different sizes are inpainted with different levels of surrounding information. The results showed that an almost unrecognizable image can be recovered with visually good result. The algorithm can be further extended for processing motion picture with high percentage of noise.
文摘Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding with edge alignment. This method uses blocks of size 4 × 4 and its basic idea is to find motion vector using the edge position in each video coding block. The method finds the motion vectors more accurately and faster than any known classical method that calculates all the possibilities. Our presented algorithm is compared with known classical algorithms using the evaluation function of the peak signal-to-noise ratio. For comparison of the methods we are using parameters such as time, CPU usage, and size of compressed data. The comparison is made on benchmark data in color format YUV. Results of our proposed method are comparable and in some cases better than results of standard classical algorithms.
