SoonKeun Chang

Histogram based ghost removal in high dynamic range images

Multiple images with different exposures are used to produce a high dynamic range image (HDRI). When a user captures an image sequence, the ghost effect caused by moving objects and background change appears in an HDRI. This paper proposes a histogram based ghost removal method, in which object motion and background change between two exposures are detected using multi-level threshoding of the intensity histogram. The detected object motion is used to determine weighting factors in construction of the radiance map. Experiments with several sets of test images with different exposures show that the proposed method gives a better performance than existing methods in terms of visual results and computation time.

Noise reduction and adaptive contrast enhancement for local tone mapping

In this paper, we propose a noise reduction method and an adaptive contrast enhancement for local tone mapping (TM). The proposed local TM algorithm compresses the luminance of high dynamic range (HDR) image and decomposes the compressed luminance of HDR image into multi-scale subbands using the discrete wavelet transform. For noise reduction, the decomposed images are filtered using a bilateral filter and soft-thresholding. And then, the dynamic ranges of the filtered subbands are enhanced by considering local contrast using the modified luminance compression function. Finally, the color of the tone-mapped image is reproduced using an adaptive saturation control parameter. We generate the tone-mapped image using the proposed local TM. Computer simulation with noisy HDR images shows the effectiveness of the proposed local TM algorithm in terms of visual quality as well as the local contrast. It can be used in various displays with noise reduction and contrast enhancement.

Tone mapping using color correction function and image decomposition in high dynamic range imaging

In this paper, we propose a tone mapping (TM) method using color correction function (CCF) and image decomposition in high dynamic range (HDR) imaging. The CCF in the proposed TM is derived from the luminance compression function with the color constraint under which the color ratios, between the three color channels of the radiance map and dynamic range compression term, are preserved and color saturation is controlled. The proposed CCF is developed to locally perform the luminance compression and color saturation control in local TM. For image decomposition, we use a bilateral filter and apply the adaptive weight to the base layer of the luminance. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality as well the local contrast. It can be used for contrast and color enhancement in various display and acquisition devices.

Noise reduction in high-ISO images using 3-D collaborative filtering and structure extraction from residual blocks

This paper proposes a noise reduction method in digital camera images at high-International Organization for Standardization (ISO) setting. Noise characteristics of luminance and chrominance channels in high-ISO images are different, so we decompose an image into luminance and chrominance channels and process them differently. With luminance image, we perform three-dimensional (3-D) collaborative filtering and structure extraction from residual blocks. The proposed method groups similar two-dimensional blocks into 3-D arrays for collaborative filtering in the transform domain. Residual blocks obtained by 3-D collaborative filtering contain structure residual as well as noise. A modified joint image-noise filter is used to extract structure residual from residual blocks. Finally, denoised blocks and structure residual blocks are returned to their original locations. To process overlapping blocks obtained from 3-D filtering and structure extraction, aggregation is used. Chrominance images at high-ISO setting are observed to have coarse-grain noise. To reduce color noise, we use a multiresolution framework, where chrominance images are decomposed into low- and high-frequency subbands. 3-D collaborative filtering is applied to low-frequency subband whereas hard-thresholding is used in high-frequency subbands. Experimental results with various test images at high-ISO setting show that the proposed method gives better subjective visual quality than other state-of-the-art image denoising methods.

Estimation of motion blur parameters using cepstrum analysis

In this paper, we propose a novel estimation method of the parameters of motion blur, which is caused by the camera or object motion during the image and video capture. In the proposed method, the motion blur is characterized by the blur orientation and length in cepstrum domain. To a better estimation of orientation and length of the motion blur in the cepstrum domain, we use the difference of Gaussian as the input of the cepstrum transform, without additional transform such as Hough or Radon transform. We propose a simple and effective method, which separates blur components from image components. Simulations with various sets of simulated and real motion blurred images show the effectiveness of the proposed algorithm in terms of the quality. The proposed algorithm is computationally efficient and easy to use.

Local tone mapping using luminance compression and adaptive color saturation control parameter

In this paper, we propose a new local tone mapping (TM) algorithm, which combines luminance compression function with an adaptive color saturation control parameter. The luminance of the radiance map is decomposed by a bilateral filter and compressed by the modified luminance compression function. To generate color channels of the tone mapped image, we use color ratios and color saturation control parameter along with the compressed luminance. The proposed TM algorithm enhances details and color representation as well as suppresses the color artifact. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality and the color reproduction. The proposed algorithm is computationally efficient and easy to use. It can be used for contrast enhancement and color artifact suppression in various display and acquisition devices.

Improved histogram based ghost removal in exposure fusion for high dynamic range images

For producing a single high dynamic range image (HDRI), multiple low dynamic range images (LDRIs) with different exposures are used. In high dynamic range imaging, a moving object in a set of LDRIs causes the ghost effect in a final HDRI. In this paper, we propose a ghost removal method based on histogram information. Object motion is detected by comparing ranks of intensity between LDRIs, and then the generated motion map is combined to construct the weight map in exposure fusion. Experimental results using various sets of LDRIs show that the proposed method effectively removes ghost effect and enhances contrast in a final HDRI. In terms of the computation time, the proposed method gives a better performance than existing methods.

Tone mapping with contrast preservation and lightness correction in high dynamic range imaging

In real-world environments, the human visual system perceives a wide range of luminance in a scene. However, the full range of tones in a high dynamic range (HDR) scene cannot be displayed on standard display devices due to their low dynamic range (LDR). Therefore, tone mapping is necessary to faithfully display a HDR scene on an LDR display device. Existing tone mapping methods have problems because details and contrast in a scene are not preserved faithfully, and they also distort the colors in a scene. Thus, we propose a tone mapping method for preserving the detail in an HDR scene using a weighted least squares filter, which preserves the global contrast in a scene by using a competitive learning neural network, before applying a tone reproduction operator to preserve the color without shifting the lightness. According to the Helmholtz–Kohlrausch effect, the perception of brightness depends on the lightness, chroma, and hue of a color. For example, the luminance of pixels with specific colors such as red and blue is low in an HDR scene. The proposed method corrects the lightness of pixels according to the color (i.e., lightness, chroma, and hue) of a tone-mapped image. Experimental results with several test sets of images demonstrated that the proposed tone mapping method with contrast preservation and lightness correction is more suitable for dynamic range compression than existing tone mapping methods, while it also preserves the color of a scene in an effective way.

Noise reduction using multiscale bilateral decomposition for digital color images

In this paper, we propose a noise reduction algorithm for digital color images using a nonlinear image decomposition approach. Most existing noise reduction methods do not adequately consider spatial correlation of color noise in digital color images. Color noise components in color images captured by digital cameras are observed as irregular grains with various sizes and shapes, which are spatially randomly distributed. We use a modified multiscale bilateral decomposition to effectively separate signal and mixed-type noise components, in which a noisy input image is decomposed into a base layer and several detail layers. A base layer contains strong edges, and most of noise components are contained in detail layers. Noise components in detail layers are reduced by an adaptive thresholding function. We obtain a denoised image by combining a base layer and noise-reduced detail layers. Experimental results show the effectiveness of the proposed algorithm, in terms of both the peak signal-to-noise ratio and visual quality.

Combined luminance compression and color constraint for color correction in tone mapping

In this paper, we present a general color correction function (CCF) in tone mapping (TM), which combines luminance compression and color constraint at locally prespecified luminance level. The proposed CCF is derived from the luminance compression function with the color constraint under which the color ratios between the three color channels are preserved and color saturation is controlled. The proposed CCF is developed to locally perform the luminance compression and color saturation control in local TM. Computer simulations with various sets of real, low dynamic range images show the effectiveness of the proposed TM algorithm in terms of the visual quality as well the local contrast.