In-Su Jang

Adaptive color enhancement based on multi-scaled Retinex using local contrast of the input image

Methods of contrast enhancement and color correction are currently among the most active fields in imaging research. The tone curve or histogram of an image is generally used to improve contrast and detail, even though this is often unsatisfactory because the intensity and chromaticity of the illumination vary with geometric position. This has led to the development of the multi-scaled Retinex algorithm in which the in fluence of non-uniform illumination is reduced by partitioning the original image using local average images that are estimated ba sed on Gaussian filtering. However, this algorithm produces color distortion because of the dominant chromaticity of the illumination. To solve this problem, this study introduces a new color correction method for digital images inspired by the multi-scale Retinex algorithm. The method includes selecting appropriate parameters for the Gaussian filters because this is the most important factor in reducing the artifacts introduced by the conventional multi-scale Retinex algorithm. Measures of visual contrast and halo are used to check the condition of artifacts for different values of the Gaussian parameters. The illuminant component is estimated to correct its chromaticity. A saturation compensation method based on preserving the chroma ratio is also used to compensate for the possible lack of saturation resulting from the modified multi-scale Retinex model.

Robust subpixel shift estimation using iterative phase correlation of a local region

In this paper, subpixel shift estimation method using phase correlation with local region is proposed for registration of noisy images. Commonly, phase correlation based on the Fourier shift property is used to estimate the shift between images. Subpixel shift of images can be estimated by the analysis for the phase correlation of downsampled images. However, in case of images with noise or aliasing artifacts, the error in estimation is increased. Thus, we consider a small region in a corner of an image instead of the whole, because flat regions with noise and regions with aliasing induce the error of estimation. In addition, to improve accuracy, the local regions are inversely shifted by varying the subpixel shift values, and obtaining the peak value of phase correlation between the images. Then, the subpixel shift value corresponding to the maximum of the peak values is selected. Real-time implementation of this process is possible because only a local region is used, thereby reducing the process time. In experiments, the proposed method is compared with conventional methods using several fitting functions, and it is applied for the task of super resolution imaging. The proposed method shows higher accuracy in registration than other methods, also, edge-sharpness in superresolved images is improved.

Subpixel shift estimation in noisy image using a wiener filtered local region

Image registration is a fundamental technique in image processing that requires a precise shift estimation with subpixel accuracy. However, when an image is affected by noise, aliasing, or other artifacts, this increases the estimation error. Accordingly, a novel accurate subpixel shift estimation method is proposed for the registration of noisy images. In the proposed method, instead of using the whole noisy image, a local region is selected based on analyzing the gradient and distribution of the frequency component in the vicinity of a corner. Next, an adaptive Wiener filter, where the window size is varied depending on the property of the local region, is applied to suppress remaining noise. Finally, an iterative phase correlation of the selected local region is performed within a restricted range using a coarse to fine method. In experiments, the proposed method provides a higher estimation accuracy than other methods. Plus, when applying the proposed method to the registration of super resolution, an enhanced edge sharpness is seen in the resulting images.

Hi-Fi Printer Characterization Method using Color Correlation for Gamut Extension

This paper proposes a colorimetric characterization method using the color correlation between the colorants in a hi-fi printer. While several colorant combinations can be used to match a certain color stimulus in a hi-fi printing system with more than 3 colorants, conventional colorimetric characterization methods only use 3 or 4 colorants to render a color, thereby limiting the color representation. As a result, the gamut is limited as they give up the other combinations of colorants. Therefore, this paper proposes a method of colorimetric characterization that uses combinations of all the colorants. As such, certain colorant combinations are selected based on considering the correlation factor between the colorant amount distributions. The correlation factor also affects the interpolation error, as the colorants are not independent of each other. Consequently, the total gamut is increased in low lightness regions, and the colors are represented more accurately.

Colorimetric characterization based on color correlation in CMYKGO printer

This paper proposes a method of colorimetric characterization based on the color correlation between the distributions of colorant amounts in a CMYKGO printer. In colorimetric characterization beyond three colorants, many color patches with different combinations of colorant amounts can be used to represent the same tri-stimulus value. Therefore, choosing the proper color patches corresponding each tri-stimulus value is important for a CMYKGO printer characterization process. As such, the proposed method estimates the CIELAB value for many color patches, then selects certain color patches while considering high fidelity and the extension of the gamut. The selection method is divided into two steps. First, color patches are selected based on their global correlation, i.e. their relation to seed patches on the gray axis, and become the reference for correlation. However, even though a selected color patch may have a similar overall distribution to the seed patch, if the correlation factor is smaller than the correlation factors for neighboring patches, the color patch needs to be reselected. Therefore, in the second step, the color patch is reselected based on the local correlation with color patches that have a lower correlation factor with the seed patch. Thus, to reselect the color patch, the seed patch is changed to the average distribution of eight neighboring selected color patches, and the new color patch selected considering the new correlation factor. Consequently, the selected color patches have a similar distribution to their neighboring color patches. The selected color patches are then measured for accuracy, and the relation between the digital value and the tristimulus value for the color patches stored in a lookup table. As a result of this characterization, the gamut is extended in the dark regions and the color difference reduced compared to conventional characterization methods.

Photo-inkjet printing method based on limited colorant amount and dot-visibility ordering

This paper proposes a method for reducing unnecessary colorant usage based on limiting the total-colorant quantity and dot-visibility ordering. First, CIELAB values are estimated for an input RGB image using a color-mixing model, and then compared with pre-calculated CIELAB values corresponding to all combinations of the CMYKlclm colorants using a color-difference constraint, thereby determining the initial CMYKlclm candidates. Next, a limitation on the total-colorant quantity is imposed on the initial CMYKlclm candidates to prevent a poor edgesharpness, and the final CMYKlclm candidates are then determined based on different dot-visibility orderings of C, M, Y, K, lc, and lm to reduce the use of excessive amounts of colorants. Experiments show that the proposed method can effectively reduce excessive colorant usage, while preserving a good image quality.

Adaptive color reproduction method to various users' monitor environment in color printer

In current printing technique, the Color Management System uses the ICC profiles of monitor and printer to perform color matching. Unfortunately the ICC profile cannot capture all of the monitor color reproduction characteristics, because such features change when the user acts on the color temperature, brightness and contrast controls, and they also depend on the kind of backlighting and lifetime of LCD monitor. As a result there is usually an unwanted color difference between an image displayed on the user monitor and its printed version. Yet, once we are able to produce an ICC profile that matches the users monitor characteristics by measuring, then the CMS becomes able to correctly perform color matching. However, this method is of difficult application, because in general the measuring equipment is not available and, even then, it takes a long time and new measurements according to monitor color temperature, brightness and contrast. In this paper we propose a color matching technique based on estimate of the users environment through the simple visual test with an output image on monitor and its printed image. The estimated characteristic of monitor is stored in new ICC profile and applied to color conversion process. Consequently the proposed method reduced the color difference between image displayed on user monitor and its printed image.