Sungmok Lee

A Space-Variant Luminance Map based Color Image Enhancement

Improvement of image quality has been highly demanding for users in digital imaging systems. A variety of image enhancement algorithms has been developed to control image enhancement factors. This paper presents a color image enhancement method that makes use of a space-variant luminance map (SVLM) for the local brightness characterization. Two-dimensional gamma correction combined with the SVLM is developed to increase the intensity at the dark region and vice versa at the bright region in the luminance domain. The enhanced luminance information is applied to the adaptive contrast enhancing process and the linear color restoration. The proposed algorithm reveals details of the input image as well as minimizes loss of the edge sharpness in the non-uniform and low illumination conditions. The developed enhancement process resulted in the lowest absolute mean brightness error (AMBE) in a low-complexity fashion. A series of experimental results are discussed in terms of visual quality, the enhancement performance, and the complexity.

Color Image Enhancement Based on Adaptive Nonlinear Curves of Luminance Features

This paper proposes an image-dependent color image enhancement method that uses adaptive luminance enhancement and color emphasis. It effectively enhances details of low-light regions while maintaining well-balanced luminance and color information. To compare the structure similarity and naturalness, we used the tone mapped image quality index (TMQI). The proposed method maintained better structure similarity in the enhanced image than did the space-variant luminance map (SVLM) method or the adaptive and integrated neighborhood dependent approach for nonlinear enhancement (AINDANE). The proposed method required the smallest computation time among the three algorithms. The proposed method can be easily implemented using the field-programmable gate array (FPGA), with low hardware resources and with better performance in terms of similarity.

New video enhancement preprocessor using the region-of-interest for the videoconferencing

The development of audio/video compression systems has made feasible digital multimedia applications. Under limited bandwidth environments, the human visual attention using region-of-interest (ROI) has been reported to improve the performance in the video coding. In this paper, we propose a ROI based video preprocessor method that deals with the perceptual quality in a low-bit rate communication environment. Three separated processes of the ROI detection, the image enhancement, and the boundary reduction are proposed to deliver better video quality at the videoconferencing application for use in a fixed camera and to be compatible as a preprocessor with the conventional video coding standards. A series of the simulation results and the subjective quality comparison assessment are discussed to show the quality improvement.

A New Approach to Color Adjustment for Mobile Application Displays with a Skin Protection Algorithm on a CIE1931 Diagram

Mobile displays use liquid crystal displays (LCDs). Such displays have various problems, such as narrow color gamut and color saturation. We propose an algorithm to solve these problems by using data processing without panel replacement. In general, the subtle problems in color adjustment are skin color conversion and color saturation. The human skin tone is the color that is typically remembered; viewers feel awkward when skin colors are converted to unnatural colors. This paper proposes as a solution a skin protection algorithm that detects human skin colors and protects skin colors from changing. It also introduces adaptive quadratic curves that reproduce natural appearances more vividly without color saturation. In addition, the system does not use field-to-field processing but pixel-to-pixel processing in real time so that the incoming image can be displayed without field flickering

Color image enhancement method using a space-variant luminance map

This paper presents a method for improving the contrast of color images. A variable and nonlinear gamma characteristic is applied to the input image, depending on the local dependency of the intensity. In this work, we present a local contrast correction algorithm that allows for simultaneous low-light region and high-light region adjustments, based on simple pixel-wise gamma correction. Also, to minimize the change in color saturation between the input and the output image, we present the applied local characteristic.

Implementation of the Gamma (γ) Line System Similar to Non-linear Gamma Curve with 2bit Error(LSB)

Gamma correction is an essential function in every display device such as CRT, plasma TV, and TFT LCD. (Po-Ming Lee, 2005) proposed gamma (γ) correction systems are developed to reduce the difference between non-linear gamma curve produced by a typical formula and result produced by the proposed algorithm. The proposed algorithms and systems are based on the specific gamma value such as 2.2, namely the formula, f(x)=xγ and the bit width of input and out data is 10bit. In order to reduce the difference, the proposed system is using the least squares polynomial which is calculating the best fitting polynomial through a set of points which is sampled. System are consisting of continuous several kinds of equations and having their own overlap sections to get more precise. Based on the algorithm verified, the systems are implemented by using Verilog-HDL. This paper compares the latest algorithm such as proposed system with the previous that of gamma system such as existing system. The former and the latter system have 2, 2 clock latency; each 1 result per clock. Each of the error range (LSB) is -1~+1, -3~+4. Under the condition of SAMSUNG STD90 0.35 worst case, each gate count is 2,564, 2,083 gates and each maximum data arrival time is 17.52,15.56 [ns], respectively

An Effective Noise Estimator for Use in Noise Reduction

Conventional noise reduction filtering schemes realize limited improvements of the peak signal-to-noise ratio (PSNR) in the low-level noisy images. The flatness degree and the edge information are effectively used to estimate the noise volume. We propose a noise estimator for reducing noise in the AWGN (additive white gaussian noise) corrupted images using three intermediate image maps (FGM(flatness gray map), FIM(flatness index map), NEM(noise estimate map)). The proposed noise estimator is fed into the conventional noise reduction filters as a pre-processor. The performance of noise reduction is tested in the various AWGN corrupted images.

Implementation of memory-free skin-detection system for mobile display device

This paper proposes a simple yet extremely good technique for skin color extraction in images. This technique also allows for changeable mode options so that significantly better skin detected images are able to be obtained. The correlation between Cb and Cr is analyzed, and then a novel human skin color space is created to process 1-D skin detection properly. This system uses only a distribution of Cb and Cr from human skin, which is transformed from RGB color space, so that it is able to be applied to relatively small hardware, like mobile apparatuses.