6th International Conference on Image Processing and Its Applications 1997
DOI: 10.1049/cp:19970897
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A generic 2D sharpness enhancement algorithm for luminance signals

Abstract: In this paper we attempt to generalize a sharpness enhancement technique for TV applications. Basically, the enhancement is accomplished by adding overshoot to luminance edges. However, the optimal amount of overshoot added for a high image quality depends on the local image statistics. For this purpose, four properties of the video signal are analysed locally by separate units and depending on this analysis, we regulate the amount of sharpness enhancement to be provided. Due to these additional controls, the … Show more

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Cited by 17 publications
(12 citation statements)
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“…(4) The proposed sharpening technique clearly shows better selective sharpness enhancement capabilities and restores a sharpened image that is sharper, in which random noise is not very conspicuous, and which also has visually better picture quality than existing sharpness enhancement techniques such as the peaking method [1,2].…”
Section: Discussionmentioning
confidence: 96%
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“…(4) The proposed sharpening technique clearly shows better selective sharpness enhancement capabilities and restores a sharpened image that is sharper, in which random noise is not very conspicuous, and which also has visually better picture quality than existing sharpness enhancement techniques such as the peaking method [1,2].…”
Section: Discussionmentioning
confidence: 96%
“…In addition, the sharpness enhancement capability can be strengthened to a certain extent by introducing a technique for adaptively controlling the value of the peaking coefficient α(x,y) according to the image contents or degree of image distortion [2]. As this kind of adaptive peaking method, a technique has been devised [2] that takes into consideration the noise visibility, brightness adaptability, input signal sharpness, signal-to-noise ratio, and peaking coefficient clipping to determine a coefficient ρ(x,y)…”
Section: Gaussian Blur Function and The Peaking Methodsmentioning
confidence: 99%
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“…-horizontal and vertical scaling of video to any -adaptive noise reduction; -sharpness improvement [2] for both luminance and -low-cost field-rate conversion ("digital scan").…”
Section: Memory Bandwidth Limitationmentioning
confidence: 99%