Minsung Kang

CIECAM02-based tone mapping technique for color image contrast enhancement

We propose a CIECAM02-based tone mapping technique for color image contrast enhancement that works especially well in bright surrounding conditions. The CIECAM02 is inherently strong when considering human visual systems (HVS) and surrounding conditions. In general, dark regions look darker in bright surrounding conditions, so some details in these dark regions tend to disappear. To overcome this problem, we propose a global tone mapping technique for color image contrast enhancement that uses a gamma encoding and the I/O relationship of the CIECAM02 in bright surrounding conditions. The proposed method makes the contrast of the source image stronger in bright surrounding conditions. We confirmed the superior performance of the proposed method in bright surrounding conditions by psychophysical experiment.

An illumination invariant skin-color model for face detection

Face detection is an important step towards a fully automatic face recognition system. Among existing techniques in the literature, methods based on skin-color information have shown computational effectiveness as well as robustness in terms of rotation, scaling and partial occlusion. However, due to color variations resulted from illumination changes, many color-based techniques have yet to demonstrate a stable state of performance. In this paper, we present an illumination invariant color space model to address the color variation issue. The proposed method is evaluated both in terms of skin-color detection and face detection performances. Our empirical experiments evidenced both effectiveness and usefulness of the proposed method.

3D Video Quality Improvement for 3D TV using Color Compensation

In this paper, we have studied the color compensation method for 3D that enables 3D color presentation similar to 2D. The color compensation method uses the difference of color presentation in 2D and 3D mode. First, the RGB I/O relationship curve was derived in 2D and 3D mode based on the input RGB color bar images. The relationship was modeled in modified power-law forms. Based on the modeling information, we generated color mapping tables, which can be used for compensating the difference of colors. The proposed color mapping block can be added at the output block of a 3DTV system, where the 2D content can be bypassed but the 3D content RGB data can be processed using the color mapping table. The experimental results show that the proposed method improves color presentation of a 3DTV system using a proper color compensation based on 2D presentation.

Surrounding adaptive color image enhancement based on CIECAM02

In this paper, we propose a CIECAM02-based color image enhancement method which is particularly robust to scenes with bright surrounding. The proposed method detects color edges using a distance metric based on the characteristics of a human visual system (HVS). The CIECAM02 is inherently strong considering both HVS and surrounding conditions. A major problem of HVS is that the dark region appears darker under a bright surrounding condition, leading to masking of details within the dark region. This phenomenon causes deterioration of edges which are among the most important and sensitive components for the HVS. To overcome this problem, we propose to weight the deteriorated edges at bright scenes. Adaptively, we estimate the surrounding image by the CIECAM02, and then use a vector gradient edge detector with a newly proposed distance metric to perform the weighting. The proposed method is seen to enhance edges without introducing unwanted color artifacts. We subjectively confirm the performance with clearly enhanced images.

EMCCD color correction based on spectral sensitivity analysis

The sensor response function of a color camera is very essential to understand an overall camera imaging pipeline and to process captured images. It is also true when we characterize underlying imaging behaviors of the electron multiplying charge coupled device (EMCCD) camera, which was recently proposed to acquire color images in low-light-level conditions. Unlike existing CCD cameras, the EMCCD camera contains partially uni-modal spectral sensitivity functions (SSFs), some of which consists of two base (bi-modal) functions, thus often leading to a serious color distortion in existing characterization techniques. To address this problem, we propose a novel method that corrects output colors of the EMCCD camera by analyzing its partially uni-modal characteristics. Specifically, our goal is to correct such color distortion by adjusting bi-modal SSFs to be uni-modal. We remove the secondary region of bi-modal channels using a pre-calculated spectral sensitivity of the EMCCD camera. Experimental results demonstrate that the proposed method reduces the color distortion as well as enlarges a color gamut, which is crucial to color reproduction.

Image Color Registration for Illumination-Robust Pattern Recognition

Image-based pattern recognition techniques have attracted much attention in vision-based applications. Color-based methods have shown several benefits. However, due to color variations resulting from illumination changes, many color-based techniques have yet to demonstrate stable performance. For illumination-robust pattern recognition, we propose an image color registration method based on an image acquisition model. Since the image acquisition model is created using the variables related to an illumination condition, camera characteristics, and an object’s surface reflectance, the proposed method normalizes the image’s color by taking into account both the illumination and camera characteristics. To evaluate the performance of the proposed method in terms of illumination-robust pattern recognition, we perform both an image similarity test and a feature similarity test between images acquired under different illumination conditions. Through the experiments, the superiority and the usefulness of the proposed method was validated.

Lens simulation with light field camera

We introduce the post processing method for virtual lens which simulates the focal length with super resolution and image stitching algorithm as well as the aperture with light-field rendering and lightness perception. Experimental results show the effectiveness of the cost less reconstruction technique for handling plenty of ordinary lenses.