Ricerc@Sapienza

This paper aims at increasing the visual quality of a blurred image according to the contrast sensitivity of a human observer. The main idea is to enhance those image details which can be perceived by a human observer without introducing annoying visible artifacts. To this aim, an adaptive wavelet decomposition is applied to the original blurry image. This decomposition splits the frequency axis into subbands whose central frequency and amplitude width are built according to the contrast sensitivity.

The paper presents a method for color quantization (CQ)which uses visual contrast for determining an image-dependent colorpalette. The proposed method selects image regions in a hierarchicalway, according to the visual importance of their colors with respect to thewhole image. The method is automatic, image dependent and requires amoderate computational effort. Preliminary results show that the qual-ity of quantized images, measured in terms of Mean Square Error, ColorLoss and SSIM, is competitive with some existing CQ approaches.