A Robust Algorithm for Color Correction between Two Stereo Images

Wang, Qi; Wang, Zengfu

doi:10.1007/978-3-642-12304-7_38

Cited by 16 publications

(16 citation statements)

References 13 publications

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“…In addition to color features, spatial information is utilized in order to identify corresponding regions between images. [21][22][23][24] Roettger et al 22 proposed a color transfer that extends the existing histogram based method by incorporating the spatial information of a 3D volume into the histogram. The method developed by Chiou and Hsu 21 uses multiple reference images to determine the best corresponding region for the target image.…”

Section: Image Color Adjustment Using Both Color and Spatial Featuresmentioning

confidence: 99%

Image color adjustment for harmony with a target color

Kim

Suk

2017

Color Research & Application

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Although a number of methods have been developed for image adjustment in various applications, very little work has been done in the context of visual design. In this regard, this article introduces a novel and practical context of image color adjustment and develops a method to adjust an image for harmony with a target color. The experiment with designers revealed that designers made significant changes in hue dimension, and preferred to promote color similarity between the image and the target color. Based on insights from designers, we proposed a method to achieve a harmonious combination of an image and a color element by increasing the hue similarity between them. The result of a user test revealed that our method is particularly useful for images with nonliving objects but less effective for images involving human skin, foods, and so on. It is expected that the practical context investigated in this study can promote a variety of related studies that satisfy the tangible needs of industries and academia. K E Y W O R D Scolor transfer, harmony, hue similarity, image color adjustment, visual design | I NT ROD UCTI ONImage adjustment encompasses a wide range of techniques, such as photo quality enhancement, color adjustment, and image stitching. In particular, editing colors in an image has received extensive attention due to the compelling power of colors upon the aesthetics and impressions of an image. A number of methods have been proposed to modify the colors based on reference images, color palettes, and users' manual inputs. By transferring the colors of one image to another, these methods aim at resembling the look and/or style of given examples.In the practice of visual design, however, color adjustment is often performed with a distinct purpose in mind. For instance, designers are frequently asked to perform a series of design works related to a corporate identity or a brand. 1,2 In such tasks, the use of color is constrained by the brand identity. [3][4][5] Figure 1 shows design cases for international companies or organizations. As shown, a specific color or a color theme is dominantly used throughout the design works. In order to communicate their identity persuasively, it is important to use images that can create aesthetics and a visual harmony with the color. These examples imply a need for image adjustment in consideration of harmony with a given color. However, harmonious image adjustment has yet to be investigated, despite its practicality and usefulness in various applications.In this regard, we made a novel attempt to develop an algorithm that adjusts the colors of an image to achieve harmony with a target color. To achieve this goal, we first benchmarked the image adjustment process of designers and built a framework of our image adjustment method based on their insights. We developed its details by adopting the technical approaches of earlier color transfer studies. Finally, a user test was carried out to examine the performance of our method in the context of graphic design.Thro...

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Section: Image Color Adjustment Using Both Color and Spatial Featuresmentioning

confidence: 99%

Image color adjustment for harmony with a target color

Kim

Suk

2017

Color Research & Application

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“…Unfortunately, colours are often not well matched due to several inevitable factors [12], such as non-Lambertian surfaces, non-diffused illumination and etc. To reduce matching ambiguities caused by colour discrepancies, Wang et al [27] proposed a local colour correction method. In their method, the source image was segmented into several regions and the SIFT features were matched between stereo images using an optical-flow based matching algorithm.…”

Section: Related Workmentioning

confidence: 99%

Robust region‐wise colour correction method for stereo matching

Ran

Zhao

Feng

2016

IET Computer Vision

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Significant colour discrepancies between stereo images have severe impacts on stereo matching algorithms, which depend on colour similarity. To address this problem, a region-wise colour correction method is proposed in this paper. First, the source image, which is to be corrected, is segmented into a set of regions using the mean-shift method. SIFT features are extracted from both the source image and the reference image, and then matched. The matched SIFT pairs are refined by exploiting epipolar geometry constraint. Based on the segmentation result and the refined SIFT matches, the regional correspondences between two stereo images are estimated. Then, each matched region pair is used to compute a local colour correction function. A set of colour weight maps is calculated for these functions. Last, to alleviate the colour transformation discontinuities along the region boundaries and facilitate a smooth colour correction globally, the corrected colour is obtained by combining the colour correction functions using the colour weighting maps. We apply the proposed local colour correction method to stereoscopic images before conducting stereo matching. The results indicate that the proposed algorithm can effectively and robustly alleviate the colour discrepancies, and improve the accuracy of stereo matching.

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“…In addition, the favorite color correction method for reference colors was proposed [13]. Color calibration methods for stereoscopic images have been studied in order to balance the colors between the left and right images [14] [15]; however, few studies have been carried out to correct the color degradation that results from 3D reproduction.…”

Section: Introductionmentioning

confidence: 99%

Normalized tone-mapping operators for color quality improvement in 3DTV

Kim

Jung

Ham

et al. 2014

2014 9th IEEE Conference on Industrial Electronics and Applications

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A normalized tone-mapping method that can reproduce a 3DTV image with an improved color sensation is proposed. This method uses 128 levels of gray-scale images to measure the RGB tone-curves in both 2D and 3D modes and then models the curves using a piece-wise linear form. To compensate the difference between these two tone-curve models, tonemapping operators are generated. In addition, the tone-mapping operators are normalized to reduce distortions in the color contrast. Experimental results show an 8.49dB improvement of image quality as compared with a conventional 3DTV.

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A Robust Algorithm for Color Correction between Two Stereo Images

Cited by 16 publications

References 13 publications

Image color adjustment for harmony with a target color

Image color adjustment for harmony with a target color

Robust region‐wise colour correction method for stereo matching

Normalized tone-mapping operators for color quality improvement in 3DTV

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