Abstract
This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengthens the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved.
Highlights
Many psychological and physiological studies have reported that human visual neurons accept visual signals in frequency components; human visual perception is primarily affected by the frequency energy distributions of images [13,14]
We develop a detail image signal enhancement method that recursively increases the perceptual contrast (PC) and simultaneously intensifies the granular signals
We exploited the human perceptual contrast that measures the sensitivity of human visual perception to frequency components
Summary
Humans recognize more sharpened images as being clearer and perceive images embedding finely resolved signals as being higher resolution images, even at the same resolution. The spatial domain methods usually enhance the local contrast for the images to become clearer, they rarely enhance images to be finely resolved. Domain as the frequency band increases [5] This method sharpens local variant signals in line with human visual perception, but rarely makes images seemed more resolved. Since the method processes detail signals globally, it may produce insufficiently enhanced textures or excessively boosted noises It is not easy in actual systems to take the DCT over the entire image. To increase the sharpness of local variant signals, we devise a recursive frequency energy scaling-up method from the perceived contrast model that indicates the visual sensitivity of detail signals in the frequency domain.
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