Research Journal of Applied Sciences, Engineering and Technology 4(24): 5515-5518, 2012 ISSN: 2040-7467 © Maxwell Scientific Organization, 2012 Submitted: March 23, 2012 Accepted: April 30, 2012 Published: December 15, 2012 Corresponding Author: K. Dinesh, J. P College of Engineering, Ayikudi, Tirunelveli, Tamilnadu, India 5515 Color Image and Video Compression Based on Direction Adaptive Partitioned Discrete Wavelet Transform K. Dinesh, S. Saravana Kumar and P. Daniel J.P. College of Engineering, Ayikudi, Tirunelveli, Tamilnadu, India Abstract: The main objective of this study is to use the Direction-Adaptive Partitioned Block Transform (DA-PBT) for compressing the color images and videos. It is same as the direction-adaptive block transform but it also have an additional direction-adaptive block partitioning to improve energy concentration. The selection of a directional mode determines the transform direction that provides directional basis functions. It reduces complexity and more efficient coefficient ordering for entropy coding. For image coding, the DA-PBT significantly outperforms the directional DCT. As a block transform, the DA-PBT can be directly incorporated into the prediction-based video coding standards to work with the block-based intra prediction as well as the block-based motion-compensated interframe prediction. The performance of the DA-PBT is compared with the 2D-DCT by using the Peak-Signal-to- Noise Ratio (PSNR) and Compression Ratio (CR). The experimental results shows that the DA-PBT performs well than the 2D-DCT. Keywords: Compression techniques, discrete wavelet transforms, video coding standards INTRODUCTION Image compression has been the key technology for transmitting massive amount of real-time image data via limited bandwidth channels. The data are transferred in the form of image, graphics, audio and video. These types of data have to be compressed during the transmission process. Otherwise the data need a large storage capacity and transmission bandwidth if it is uncompressed. Huge amount of data can’t be fit if there is low storage capacity present. To solve this problem the data has to be compressed by using any one of the algorithms and then it can be sent easily. Data compression is the process of converting an input data stream into another data stream that has smaller size. There are two types of image compression: lossless and lossy. With lossless compression, the original image is recovered exactly after decompression. Much higher compression ratios can be obtained if some error, which is usually difficult to perceive, is allowed between the decompressed image and the original image. This is lossy compression. In many cases, it is not necessary or even desirable that there be error-free reproduction of the original image. In such a case, the small amount of error introduced by lossy compression may be acceptable. Another application where lossy compression is acceptable is in fast transmission of still images over the Internet. For over two decades, block transforms such as the 2-D DCT have been the key component in image coding techniques, e.g., the JPEG standard (Information Technology, 1992). Although more recently, convolutional transforms, such as the 2-D DWT, have been proved superior (Taubman and Marcellin, 2000; Information Technology, 2002), JPEG is still the prevalent image coding format to date. Block transforms also remain an integral part in most video coding standards since they can be effectively combined with block-based motion-compensated prediction (Wiegand et al., 2003). In image coding, directional features such as lines and edges have significant impact on both the objective and the subjective performance. Block transforms are typically constructed in a separable manner, by cascading a 1-D vertical transform and a 1-D horizontal transform. Separable transforms tend to do well for image detail oriented strictly horizontally and vertically, while ringing and checkerboard artifacts are likely to appear around edges of other orientations, significantly deteriorating visual quality. To exploit directionality, the intra coding portion of the video coding standard H.264 predicts a block from previously encoded blocks using directional extrapolation (Wiegand et al., 2003) and the residual is then encoded via a block transform. This approach is effective, but it requires perfect synchronization of the DPCM loops of encoder and decoder. Any deviation between encoder and decoder can propagate over the image, leading to an