Animation video is becoming very popular with the availability of low cost computing resources. The cell animation is a popular method, used for producing animation video. In order to efficiently encode these videos, conventional video codecs, such as AutoDesk Animation Pro FLC, Intel Indeo 5, and MPEG-4 can be used to achieve high compression. However, when cell animation videos are compressed at very low bit rate by these traditional codecs, objectionable artifacts, e.g., false color, blurred contours, and blocking artifact, are severely occurred. In this paper, we propose an efficient compression method for cell animation images. The proposed method employs hybrid coding scheme which includes intraframe and interframe coding modes. The intraframe mode consists of color quantization, adaptive differential pulse code modulation, forward classification, and Golomb-Rice coding. The interframe coding consists of block-based techniques and exploits the characteristics of motion. Simulation results show that the proposed method provides superior performance over AutoDesk Animation Pro FLC, MPEG-1, Intel Indeo 5, and MPEG-4 standards.

Very high resolution images with more than 2,000*2.000 pels will play a very important role in a wide variety of applications of future multimedia communications ranging from electronic publishing to broadcasting. To make communication of very high resolution images practicable, we need to develop image coding techniques that can compress very high resolution images efficiently. Taking the channel capacity limitation of the future communication into consideration, the requisite compression ratio will be estimated to be at least 1/10 to 1/20 for color signals. Among existing image coding techniques, the sub-band coding technique is one of the most suitable techniques. With its applications to high-fidelity compression of very high resolution images, one of the major problem is how to encode high frequency sub-band signals. High frequency sub-band signals are well modeled as having approximately memoryless probability distribution, and hence the best way to solve this problem is to improve the quantization of high frequency sub-band signals. From the standpoint stated above, the work herein first compares three different scalor quantization schemes and improved permutation codes, which the authors have previously developed extending the concept of permutation codes, from the aspect of quantization performance for a memoryless probability distribution that well approximates the real statistical properties of high frequency sub-band signals, and thus demonstrates that at low coding rates improved permutation codes outperform the other scalor quatization schemes and that its superiority decreases as its coding rate increases. Moreover, from the results stated above, the work herein, develops a rate-adaptive quantization technique where the number of bits assigned to each subblock is determined according to the signal variance within the subblock and the proper quantization scheme is chosen from among different types of quantization schemes according to the allocated number of bits, and applies it to the high-fidelity encoding of sub-band signals of very high resolution images to demonstrate its usefulness.