Low bit

Abstract: A video compression/decompression procedure that provides a reliable, low bit video bit stream with some color features over relatively low bandwidth wireless networks. The procedure provides some pleasing color features in a video bit stream without needing a large bandwidth network like those needed for example for a MPEG 4 bit stream. The procedure provides the color features by using a bi-level Y luminance component and a number of UV chrominance combinations. The bi-level Y-component outlines the features of the image, while the UV-combinations describe the basic color information of the image.

Abstract: With the growing importance of low-bandwidth applications, such as wireless access to the Internet, images are often sent or received at low bit rates. At these bit rates, they suffer from significant distortion and artifacts, making it difficult for those viewing the images to understand them. We present two progressive compression algorithms that focus on preserving the clarity of important image features, such as edges, at compression ratios of 80:1 and more. Both algorithms capture and encode the locations of important edges in the images. The first algorithm then transmits a standard SPIHT (set partitioning in hierarchical trees) bit stream, and at the decoder applies a nonlinear edge-enhancement procedure to improve the clarity of the encoded edges. The second approach uses a modified wavelet transform to "remove" the edges, and encodes the remaining texture information using SPIHT. With both approaches, features in the images that may be important for recognition are well preserved, even at low bit rates.

Abstract: Peak signal-to-noise ratio (PSNR) is not a good measure of perceived picture quality, especially at low bit rates of coding. This paper proposes a new approach for computing perceptual distortion for visual signal in order to provide an objective measure for perceptual quality at low bit rate coding in typically mobile communications. The regions with three major perceptually disturbing artifacts, namely, damaged edge, blockiness and ringing, are detected as the basis of assessment. The correlation of the metric with human perception has been demonstrated with low bit rate CIF test data.