Abstract
This paper evaluates optimal quantization and data compression in the context of the end-to-end model for 2-D sampled imaging systems. Results show that the minimum number of bits (data density) required for lossless information transmission depends on the design of the image-gathering device. The information in the acquired signal, not its energy, dictates the trade-off between data transmission and visual quality. The entropy of the encoded signal does not indicate neither the amount of information conveyed by the process nor the preferable design tradeoffs for sampled imaging systems. Optimal end-to-end system design for constraint transmission inevitably involves a trade-off between electronic noise and quantization error. The resulting end-to-end design minimizes the loss of information and maximizes the efficiency of its transfer.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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