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Showing papers by "William A. Pearlman published in 1978"


Journal ArticleDOI
TL;DR: General source coding theorems are proved in order to justify using the optimal test channel transition probability distribution for allocating the information rate among the DFT coefficients and for calculating arbitrary performance measures on actual optimal codes.
Abstract: Distortion-rate theory is used to derive absolute performance bounds and encoding guidelines for direct fixed-rate minimum mean-square error data compression of the discrete Fourier transform (DFT) of a stationary real or circularly complex sequence. Both real-part-imaginary-part and magnitude-phase-angle encoding are treated. General source coding theorems are proved in order to justify using the optimal test channel transition probability distribution for allocating the information rate among the DFT coefficients and for calculating arbitrary performance measures on actual optimal codes. This technique has yielded a theoretical measure of the relative importance of phase angle over the magnitude in magnitude-phase-angle data compression. The result is that the phase angle must be encoded with 0.954 nats, or 1.37 bits, more rate than the magnitude for rates exceeding 3.0 nats per complex element. This result and the optimal error bounds are compared to empirical results for efficient quantization schemes.

85 citations


Journal ArticleDOI
TL;DR: An experiment that derives a new distortion measure from an acceptable visual system model and compares it in a fair test against squared difference in intensity in an image restoration task and shows that the filter for the new distortion measures yields a superior restoration.
Abstract: Underlying many techniques of image restortation, quantization, and enhancement is the mathematically convenient, but visually unsuitable distortion measure of squared difference in intensity. Squared-intensity difference has an indirect phenomenological correspondence in a model of the visual system. We have undertaken, therefore, an experiment that derives a new distortion measure from an acceptable visual system model and compares it in a fair test against squared difference in intensity in an image restoration task. We start with an eye–brain system model, inferred from the works of current vision researchers, which consists of a bank of parallel spatial frequency channels and image detectors. From this model we derive a new distortion criterion that is related to changes in the per-channel detection probability and phase angle. The optimal linear (Wiener) filters for each distortion measure operate in turn on the same noisy incoherent images. The results show that the filter for the new distortion measure yields a superior restoration. It is more visually agreeable, more sharply detailed, and truer in contrast compared to the squared-difference filter, and impressive in its own right. Its mathematical properties suggest that significantly increased efficiency in the storage or communication of images may be gained by its use.

28 citations