A method is presented to integrate high-resolution line graphics in the UK Teletext system. differential chain coding (DCC) enables an attractive combination of efficient graphics representation and a low-cost consume...
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A method is presented to integrate high-resolution line graphics in the UK Teletext system. differential chain coding (DCC) enables an attractive combination of efficient graphics representation and a low-cost consumer decoder. Separate graphics overlay pages are linked to the text page by means of a ‘ghost row’, a concealed row of the text page. This separation of text and graphics guarantees compatibility with the existing teletext format. One major problem of DCC is its sensitivity to errors. Two fundamentally different approaches have been considered to solve this problem: error-correcting codes and protective measures to decrease the impact of errors. Experimental results indicate the feasibility of including DCC graphics in public Teletext systems, for bit error rates up to 5 × 10-3. For the higher BERs, repeated reception of the cyclic transmissions of teletext pages appears to be essential. This leads to better results than most error-correcting codes, and the decoder can remain simple and inexpensive.
In this paper, we present a memory-efficient, contour-based, region-of-interest (ROI) algorithm designed for ultra-low-bit-rate compression of very large images. The proposed technique is integrated into a user-intera...
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ISBN:
(纸本)9780819467010
In this paper, we present a memory-efficient, contour-based, region-of-interest (ROI) algorithm designed for ultra-low-bit-rate compression of very large images. The proposed technique is integrated into a user-interactive wavelet-based image coding system in which multiple ROIs of any shape and size can be selected and coded efficiently. The coding technique compresses region-of-interest and background (non-ROI) information independently by allocating more bits to the selected targets and fewer bits to the background data. This allows the user to transmit large images at very low bandwidths with lossy/lossless ROI coding, while preserving the background content to a certain level for contextual purposes. Extremely large images (e.g., 65000 X 65000 pixels) with multiple large ROIs can be coded with minimal memory usage by using intelligent ROI tiling techniques. The foreground information at the encoder/decoder is independently extracted for each tile without adding extra ROI side information to the bit stream. The arbitrary ROI contour is down-sampled and differentialchain coded (DCC) for efficient transmission. ROI wavelet masks for each tile are generated and processed independently to handle any size image and any shape/size of overlapping ROIs. The resulting system dramatically reduces the data storage and transmission bandwidth requirements for large digital images with multiple ROIs.
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