Hyuk-Ju Kwon

Compensation of de-saturation effect in HDR imaging using a real scene adaptation model

The iCAM06, a high dynamic range rendering process, contains chromatic adaptation method based on the CIECAM02 model. The D factor, degree of adaptation, in the chromatic adaptation of the iCAM06 is the function of the adapting luminance level, but it does not consider the visual white point shift according to the variation of luminance level. The iCAM06 acquires a blurred illuminant image. So, each pixel has a different illuminant color. When some of the colors cover the entire image, a de-saturation effect appears around these colors. The simply modified D factor to reduce the de-saturation effect causes unsuitable changes in the degree of adaptation. Therefore, we propose a new method to find the global illuminant information and the D factor for the illuminant in the HDR image rendering process. Comparing the proposed with the conventional method, we confirm that the proposed method provides better illuminant estimation and color representation.

Luminance adaptation transform based on brightness functions for LDR image reproduction

Abstract Tone mapping algorithms are used for image processing to reduce the dynamic range of an image to be displayed on low dynamic range (LDR) devices. The Retinex, which was developed using multi-scale and luminance-based methods, is one of the tone mapping algorithms for dynamic range compression, color constancy and color rendition. Retinex algorithms still have drawbacks, such as lower contrast and desaturation. This paper proposes a multi-scale luminance adaptation transform (MLAT) based on visual brightness functions for the enhancement of contrast and saturation of rendered images. In addition, the proposed algorithm was used to estimate the minimum and maximum luminance and a visual gamma function for local adapted viewing conditions. MLAT showed enhanced contrast and better color representation than the conventional methods in the objective evaluations (CIEDE200 and VCM).

Radiance map construction based on spatial and intensity correlations between LE and SE images for HDR imaging

This algorithm represents an HDR image using dual exposure images.Spatial and intensity correlations estimate an accurate camera response function.The camera response function constructs a radiance map for HDR tone reproduction. HDR image was developed for the reproduction of real scenes with an acquisition of large dynamic range. In general, HDR image consists of several different exposure images according to the exposure value of a digital camera. Before the construction of a single HDR image, each input image is calibrated using CRF to convert its image data to scene radiance. In order find CRF, conventional methods require special apparatus and reference targets, or several exposure images. This paper proposes a new HDR blending algorithm that uses only dual-exposure images. The proposed algorithm is based on the least squares method, and includes spatial and intensity weighting functions. Each weighting function is used to reduce error points and improve CRF computation accuracy. In addition, a constraint is added to correct white balance in the brightness level. The rendering results show that the proposed algorithm is superior to the conventional algorithm.

Enhanced high dynamic-range image rendering using a surround map based on edge-adaptive layer blurring

Many tone-mapping methods have developed efficient tone compression and local contrast enhancement techniques for high dynamic-range imaging. Local tone mapping enhances the image quality to reveal the details; however, it causes artefacts such as halos. Halo artefacts appear around the edges of an image and lead to deterioration in the overall image quality. Detail-base separation and multi-scale methods have been developed to reduce halo artefacts. Detail-base separation methods divide the image into a detail layer and base layer using an edge-preserving filter and process each layer independently. Multi-scale methods alleviate artefacts such as halos, noise, and awkward global toning using a weighted sum of single-scale images. These methods have several inherent problems including the complexity of the edge-preserving filter and multi-processing redundancy. Therefore, in this study, a novel surround map is presented to resolve halo artefacts and enhance local details in single-scale processing.

Visual sensitivity correlated tone reproduction for low dynamic range images in the compression field

Abstract. An image toning method for low dynamic range image compression is presented. The proposed method inserts tone mapping into JPEG baseline instead of postprocessing. First, an image is decomposed into detail, base, and surrounding components in terms of the discrete cosine transform coefficients. Subsequently, a luminance-adaptive tone mapping based on the human visual sensitivity properties is applied. In addition, compensation modules are added to enhance the visually sensitive factors, such as saturation, sharpness, and gamma. A comparative study confirms that the transmitted compression images have good image quality.

Shape Extraction of Near Target Using Opening Operator with Adaptive Structure Element in Infrared hnages

Near targets in the infrared (IR) images have the steady feature for inner region and the transient feature for the boundary region. Based on these features, this paper proposes a new method to extract the fine target shape of near targets in the IR images. First, we detect the boundary region of the candidate targets using the local variance weighted information entropy (WIE) of the original images. And then, a coarse target region can be estimated based on the labeling of the boundary region. For the coarse target region, we use the opening filter with an adaptive structure element to extract the fine target shape. The decision of the adaptive structure element size is optimized for the width information of target boundary by calculating the average WIE in the enlarged windows. The experimental results show that a proposed method has better extraction performance than the previous threshold algorithms.

CAM-based HDR image reproduction using CA–TC decoupled JCh decomposition

Abstract High dynamic range (HDR) imaging has been developed for acquiring scene with a high dynamic range. Tone-mapping operators are used to reproduce the dynamic range of HDR content on a low dynamic range (LDR) devices. iCAM06 is a tone-mapping algorithm based on the color appearance model. iCAM06 contains chromatic adaptation and tone compression; however, the chrominance component of the chromatic adaptation is not preserved after tone compression. This paper describes a novel decoupled processing for the chromatic adaptation and tone compression to preserve the chrominance component and reduce the color distortion of iCAM06. Further, a color appearance model is used to separate and combine the chrominance and luminance components of the decoupled processes. The rendered results confirm that the proposed algorithm is superior to the conventional algorithm.

DCT-Based HDR Exposure Fusion Using Multiexposed Image Sensors

It is difficult to apply existing exposure methods to a resource-constrained platform. Their pyramidal image processing and quality measures for interesting areas that need to be preserved require a lot of time and memory. The work presented in this paper is a DCT-based HDR exposure fusion using multiexposed image sensors. In particular, it uses the quantization process in JPEG encoding as a measurement of image quality such that the fusion process can be included in the DCT-based compression baseline. To enhance global image luminance, a Gauss error function based on camera characteristics is presented. In the simulation, the proposed method yields good quality images, which balance naturalness and object identification. This method also requires less time and memory. This qualifies our technique for use in resource-constrained platforms.

Visual perceptual-based film-type patterned retarder three-dimensional image representation

Abstract. Film-type patterned retarder (FPR) three-dimensional (3D) displays differ from two-dimensional (2D) displays with respect to two distinct features: (1) vertical subsampling caused by a film circularly polarized on a display and (2) luminance loss caused by 3D glasses. To reveal the negative effects of these differences, we analyze the spectrum of an image on an FPR 3D display and investigate the contrast sensitivity of human vision for that image. Based on the analysis results, a preprocessing method is proposed for the aliasing problem caused by the vertical subsampling. In addition, because contrast sensitivity decreases with decreasing luminance, we propose sharpness compensation based on Barten’s contrast sensitivity function model. The proposed method performs more effectively than other methods in terms of 3D image representation.