TEMPORAL REDUNDANCY REDUCTION IN WAVELET BASED VIDEO COMPRESSION FOR HIGH DEFINITION VIDEOS

Data Storage and Communication plays a significant role in every human. Digital images and videos are stored in mobile and other storage devices. More specifically, video data requires huge amount of storage space for which the storage devices are more expensive. Hence there is a necessity of reducing the storage space of the data. Video compression is more common in all researches. In this work, the role of wavelets in video compression is studied. The temporal redundant data are converted to spatial data which are then transformed to wavelet coefficients. The low frequency components are removed from these wavelet coefficients. The proposed method is tested with some video sequences. The performance of the proposed method is analyzed by comparing it with the existing recent methods and with the state-of-art H.265 video coding standard. The experimental results substantially proved that the proposed method achieves 3.8dB higher PSNR than H.265 and 1.6dB higher PSNR than recent wavelet based video codecs

Shot Boundary Detection Using Octagon Square Search Pattern

In this paper, a shot boundary detection method is presented using octagon square search pattern. The color, edge, motion and texture features of each frame are extracted and used in shot boundary detection. The motion feature is extracted using octagon square search pattern. Then, the transition detection method is capable of detecting the shot or non-shot boundaries in the video using the feature weight values. Experimental results are evaluated in TRECVID video test set containing various types of shot transition with lighting effects, object and camera movement within the shots. Further, this paper compares the experimental results of the proposed method with existing methods. It shows that the proposed method outperforms the state-of-art methods for shot boundary detection