This paper describes picture information transmission for portable multimedia terminals. The radio links used in portable multimedia terminals have narrower channel capacity and higher transmission error rates than wired links such as those used in ISDN. To transmit multimedia information of satisfactory quality over radio links, robustness against radio link errors must be improved, because picture deterioration is much more apparent than audio deterioration. First, the effects of transmission errors on picture quality are analyzed using the H.261 coding system used for ISDN picture communication. Second, the relationship among bit error rate, terminal velocity, and picture quality is analyzed and the deterioration mechanisms of picture quality are discussed. Three techniques for improving picture quality against radio link errors are proposed.The penetration of communication services using picture information, for example, videophones and tele-conferences, has increased with progress in picture coding standardization. Miniaturization of the CPUs and advances in radio link technologies are driving the development of portable multimedia terminals using mobile communication channels. Current portable multimedia terminals mainly treat audio-signal, user data, and facsimile. Video-signal communication is expected from portable terminals as portable multimedia services become possible. These terminals will use radio links as the communication medium, and the bit error rate (BER) of those channels are much higher than those of wired channels such as ISDN. In general, since the compression ratio for video-signals is very much higher than the ratio for audio-signals, video-transmission is more sensitive than audio-transmission. For example, audio-signal quality with PSI-CELP is quite good but video-signals are heavily degraded at the BER of l02.Up to now, the deterioration in video coding-transmission has not been studied for low bit rate radio transmission. Generally speaking, the worst BER of radio links ranges from iO2 to iO. In order to transmit multimedia information, especially real-time video information, a robust video coding method and multimedia multiplexing method that maintain picture quality should be developed.In this paper, first the effects caused by bit errors are analyzed. Most coding methods, e.g. H.261, MPEG1, H.26P, differ in their quantization method and prediction method, but they basically consist of almost the same mechanisms: differentiation of successive image frames, motion compensation, discrete cosine transform (DCT), and variable length coding (VLC). Therefore, the effects are similar in those coding methods. In the applications using real-time communication, H.261 type prediction method, which uses only the previous frame, is favorable, since the processing delay time is relatively small. Thus, this 1024 ISPIE Vol. 2501 Q8194-1858-7/95/$6.00 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/15/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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SUMMARYThis paper describes a new contour line extraction algorithmwhich makes better contour line continuation and accelerates processing speed.When obtaining a contour line from an original gray-scale image, the contour line extraction algorithm generally requires the following conditions:(1) extracted contour lines representing a good feature of the original image;(2) less invalid data such as noise; (3) contour line width is one pixel thickness; and (4) better contour connectedness.Many contour line extraction algorithms have been proposed. However, usually the user has employed the contour line extraction algorithm selecting by experience and a sixth sense. In the conventional method, differential operators are carried out on an original image with thresholding at a given value. Afterward, a thinning operation is carried out to obtain a one-pixel thickness contour line. However, this process takes considerable computing time because the thinning process needs recursive processing.The new algorithm presented here carries out the process which performs the edge detection and thinning operation simultaneously eliminating the extra step. The process is effectively integrated in two ways: one is maximum point extraction in the differential image; and the other is the thresholding by introducing the selection of threshold values by using observance of the contour line connectedness in the differential image.As a result, the proposed algorithm is 10 times faster than the conventional methods in processing speed, and provides almost the same quality in contour line image.

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