Enhancing underwater image via color correction and Bi-interval contrast enhancement

Underwater captured images often suffer from color cast and low visibility due to light is scattered and absorbed while it traveling in water. In this paper, we proposed a novel method of color correction and Bi-interval contrast enhancement to improve the quality of underwater images. Firstly, a simple and effective color correction method based on sub-interval linear transformation is employed to address color distortion. Then, a Gaussian low-pass filter is applied to the L channel to decompose the low- and high-frequency components. Finally, the low- and high-frequency components are enhanced by Bi-interval histogram based on optimal equalization threshold strategy and S-shaped function to enhancement image contrast and highlight image details. Inspired by the multi-scale fusion, we employed a simple linear fusion to integrate the enhanced high- and low-frequency components. Comparison with state-of-the-art methods show that the proposed method outputs high-quality underwater images with qualitative and quantitative evaluation well.     

SIFT-flow-based color correction for multi-view video

During the multi-view video acquisition, color variation across the views tends to be incurred due to different camera positions, orientations, and local lighting conditions. Such color variation will inevitably deteriorate the performance of the follow-up multi-view video processing, such as multi-view video coding (MVC). To address this problem, an effective color correction algorithm, called the SIFT flow-based color correction (SFCC), is proposed in this paper. First, the SIFT-flow technique is used to establish point-to-point correspondences across all the views of the multi-view video. The average color is then computed based on those identified common corresponding points and used as the reference color. By minimizing the energy of the difference yielded between the color of those identified common corresponding points in each view with respect to the reference color, the color correction matrix for each view can be obtained and used to correct its color. Experimental results have shown that the proposed SFCC algorithm is able to effectively eliminate the color variation inherited in multi-view video. By further exploiting the developed SFCC algorithm as a pre-processing for the MVC, extensive simulation results have shown that the coding efficiency of the color-corrected multi-view video can be greatly improved (on average, 0.85 dB, 1.27 dB and 1.63 dB gain for Y, U, and V components, respectively), compared with that of the original multi-view video without color correction.     

Coding-oriented multi-view video color correction

Color inconsistency between views is an important problem to be solved in multi-view video applications, such as free viewpoint television and other three-dimensional video systems. In this paper, by combining with multi-view video coding, a coding-oriented multi-view video color correction method is proposed. We first separate foreground and background in first Group Of Pictures （GOP） by using SKIP coding mode. Then by transferring means and standard deviations in backgrounds, color correction is performed for each frame in GOP, and multi-view video coding is performed and used to renew the backgrounds. Experimental results ances in color correction and multi-view video show the proposed method can obtain better performcoding.     

电子航图的颜色校正技术研究

电子航图在飞行仿真领域有着重要应用,然而由于局部纸质航图尺寸、来源及扫描设备等因素的影响,扫描得到的各个子航图颜色不一致,严重影响航图的整体效果.因此本文重点讨论了电子航图的颜色校正问题,利用相郊子航图间的重重叠域,采用线性映射变换的方法,在RGB、YIQ、YUV、HIS 4种颜色空间下对电子航图进行校正和比较.实验结...     

A blind color digital image watermarking method based on image correction and eigenvalue decomposition

With the rapid development of Internet technology, the copyright protection of color images has become more and more important. In order to fulfill this purpose, this paper designs a blind color digital image watermarking method based on image correction and eigenvalue decomposition (EVD). Firstly, all the eigenvalues of the pixel block in the color host image are obtained by EVD. Then, the sum of the absolute value of the eigenvalues is quantified by the variable quantization steps to embed the color watermark image that encrypted by affine transform and encoded by the Hamming code. If the watermarked image is processed by geometric attack, then the attacked image can be corrected by using the geometric attributes. Finally, the inverse embedding process is performed to extract the color watermark. Moreover, the advantages of the proposed method are shown as follows: (1) all Peak Signal-to-noise Ratio (PSNR) values are greater than 42 dB; (2) the average Structural Similarity Index Metric (SSIM) values are greater than 0.97; (3) the maximum embedded capacity is 0.25bpp; (4) whole running-time is less than 20 s; (5) the key space is more than 2⁴⁵⁰; (6) most Normalized Cross-correlation (NC) values are more than 0.9. Compared with the related methods, the experimental results show that the proposed method not only has better watermark invisibility and larger watermark capacity, but also has higher security and stronger robustness against geometric attacks.     

Quality assessment for color correction-based stitched images via bi-directional matching

With the deepening of social information, the panoramic image has drawn a significant interest of viewers and researchers as it can provide a very wide field of view (FoV). Since panoramic images are usually obtained by capturing images with the overlapping regions and then stitching them together, image stitching plays an important role in generating panoramic images. In order to effectively evaluate the quality of stitched images, a novel quality assessment method based on bi-directional matching is proposed for stitched images. Specifically, dense correspondences between the testing and benchmark stitched images are first established by bi-directional SIFT-flow matching. Then, color-aware, geometric-aware and structure-aware features are respectively extracted and fused via support vector regression (SVR) to obtain the final quality score. Experiments on our newly constructed database and ISIQA database demonstrate that the proposed method can achieve comparable performance compared with the conventional blind quality metrics and the quality metrics specially designed for stitched images.     

彩膜Mura检测机彩色图像的应用探究

目前TFT-LCD行业彩膜产线中,宏观缺陷的在线监控与检测设备为Mura检测机.Mura检测机的原理是通过数台Line Camera和反射照明单元,读取Glass的图像并将其处理转换为灰度图像,后续由操作员对灰度图像进行观察判断,达成对Glass的宏观品质进行在线监控的目的.目前的Mura设备只能生成灰度图像,而人眼对黑白图像的辨识能力远远不如彩色图像,所以导致当相应缺陷出现在Glass边缘或操作员长时间工作后,容易出现漏检的情况,为了改善此问题,本文提出在将彩色图像应用到Mura检测机中,通过将灰度图像转化为一种"伪彩色"图像的方式,既提高了图像中缺陷的辨识程度,降低了漏检的概率,也不会因为生成彩色图像而增加图片处理时间,影响工厂的Tact Time.     

数字视频颜色校正的重要性

根据不同要求，使用应用软件对影像进行颜色校正，在后期制作中十分重要。从颜色属性、拍摄环境和摄像机造成的色差、颜色对视觉的影响和颜色校正等几个方面，叙述了颜色校正的重要性。     

Color correction and restoration based on multi-scale recursive network for underwater optical image

Underwater image processing has played an important role in various fields such as submarine terrain scanning, submarine communication cable laying, underwater vehicles, underwater search and rescue. However, there are many difficulties in the process of acquiring underwater images. Specifically, the water body will selectively absorb part of the light when light travels through the water, resulting in color degradation of underwater images. At the same time, due to the influence of floating substances in the water, the light has a certain degree of scattering, which will bring serious problems such as blurred details and low contrast to underwater images. Therefore, using image processing technology to restore the real appearance of underwater images has a high practical value. In order to solve the above problems, we combine the color correction method with the deblurring network to improve the quality of underwater images in this paper. Firstly, aiming at the problem of insufficient number and diversity of underwater image samples, a network combined with depth image reconstruction and underwater image generation is proposed to simulate underwater images based on the style transfer method. Secondly, for the problem of color distortion, we propose a dynamic threshold color correction method based on image global information combined with the loss law of light propagation in water. Finally, in order to solve the problem of image blurring caused by scattering and further improve the overall image clarity, the color-corrected image is reconstructed by a multi-scale recursive convolutional neural network. Experiment results show that we can obtain images closer to underwater style with shorter training time. Compared with several latest underwater image processing methods, the proposed method has obvious advantages in multiple underwater scenes. Simultaneously, we can restore the color information, remove blurring and boost detail for underwater images.     

Perceptual similarity between color images using fuzzy metrics

In many applications of the computer vision field measuring the similarity between (color) images is of paramount importance. However, the commonly used pixelwise similarity measures such as Mean Absolute Error, Peak Signal to Noise Ratio, Mean Squared Error or Normalized Color Difference do not match well with perceptual similarity. Recently, it has been proposed a method for gray-scale image similarity that correlates quite well with the perceptual similarity and it has been extended to color images. In this paper we use the basic ideas in this recent work to propose an alternative method based on fuzzy metrics for perceptual color image similarity. Experimental results employing a survey of observations show that the global performance of our proposal is competitive with best state of the art methods and that it shows some advantages in performance for images with low correlation among some image channels.     

颜色纠正算法在手机全景图的应用研究

针对原始图像序列曝光差异较大致使拼接痕迹明显这一问题,提出了一种新的手机全景图的颜色纠正算法,该算法通过在Ycbcr颜色空间里构造出一个全局调整函数计算出每一幅图片纠正系数,进而补偿原始图像,减弱曝光差异导致的拼接痕迹。实验结果表明,该算法不仅能快速地消除了拼接缝隙,而且使得整个全景图更自然流畅。     

大屏幕彩电中的图像孔阑校正

本文主要对大屏幕TV模拟接收机中的新型轮廓(孔阑)校正电路进行分析,文中也对孔阑失真的原因及传统孔阑校正电路给以简要的叙述,论及了实现垂直孔阑校正存在的问题。     

Efficient edge-preserving algorithm for color contrast enhancement with application to color image segmentation

In this paper, a new and efficient edge-preserving algorithm is presented for color contrast enhancement in CIE Lu^′v^′ color space. The proposed algorithm not only can enhance the color contrast as the previous algorithm does, but also has an edge-preservation effect. In addition, the spurious edge points occurred due to the color contrast enhancement can be well reduced using the proposed algorithm. This is the first edge-preserving algorithm for color contrast enhancement in color space. Furthermore, a novel color image segmentation algorithm is presented to justify the edge-preservation benefit of the proposed color contrast enhancement algorithm. Based on some real images, experimental results demonstrate the advantages of color contrast enhancement, edge-preservation effect, and segmentation result in our proposed algorithm.     

Rule-based automatic segmentation of color images

A rule-based segmentation algorithm for color images has been presented in this paper. The proposed strategy is similar to region growing algorithm where the seed points are automatically selected and grown. The similarity percents of neighboring pixels are calculated by means of fuzzy reasoning rules, and the merging of the pixels with regions is performed by comparing the similarity percent with the similarity threshold value. The algorithm does not require any prior knowledge of the number of regions existing in the image and decreases the computational load required for the fuzzy c-means (FCM). Several computer simulations have been performed and the results have been discussed. The simulation results indicate that the proposed algorithm yields segmented color image of perfect accuracy.     

应用于显示器件的动态肤色校正方法

基于输入图像中需要调整的肤色区域动态地移向特征肤色区域的图像动态肤色校正方法,提出了一种适用于显示器件中硬件实现的动态肤色校正简化模型,进而设计实现了实时动态肤色校正电路,并将其应用于100 cm彩色交流等离子体显示器(AC PDP)中进行验证。仿真及实验结果表明,本文提出的实时动态肤色校正方法能够使得校正后的输出图像中皮肤颜色显得更加自然生动,更趋近于人们对肤色的先验理解,从而有效地提高了AC PDP的彩色再现能力。     

色差图像的数字图像拼接算法

针对有明显色彩和亮度差异的图片,在进行传统的图像拼接后,会产生肉眼可见的拼接缝,严重影响拼接效果。因此,提出一种针对存在色差的图像拼接算法。首先,计算相邻图片间的色彩校正参数和每个彩色通道的全局色彩调整参数,选择适合的颜色和亮度,对每一幅图片进行色彩校正。其次,引入SIFT和RANSAC算法,实现了图像的准确配准。最后,采取0．1加权融合算法和平均融合算法结合进行图像融合,得到最终的全景图像。实验结果表明,由于已经进行图像间的校正,减少了待拼接图像的色差,使得图像的融合更加简单。该算法对于存在色差的图片序列可以实现无缝快速的拼接,并且可根据需要调整图像的色彩和亮度。     

Secure and robust host-adapted color image watermarking using inter-layered wavelet-packets

This work presents a secure and robust color image watermarking for copyright protection applications, that is based on exploiting the multi-spectral properties of the primary color components of the RGB image. The proposed scheme employs the interconnection between the subbands of the primary color components in the wavelet-packet domain. The scheme is constructed to be adaptive, in the sense that the watermark bits are embedded in safe locations, depending on the inter-layer energy of coefficients in the wavelet-packets. The scheme immunity to attacks is improved by applying a two-level security procedure. To validate the high performance of the proposed scheme, several experimental tests were conducted and a comparative analysis was provided. The obtained results have shown improved watermarking robustness against a wide range of attacks while preserving a high watermarking imperceptibility.     

Highlight‐Detection‐Based Color Correction Method for Multiview Images

In multiview imaging systems, color correction is adopted to eliminate color inconsistency between views. However, the influence of highlights on color correction has not been considered before. In this letter, a new color correction method based on highlight detection is proposed. The method is designed to treat highlight and highlight‐removal regions independently when calculating correction parameters. Finial correction is implemented with a fusion mechanism. Experimental results show that the proposed method can improve objective and subjective correction performance, while achieving better coding performance than other correction methods.     

The trinion Fourier transform of color images

Any color may be represented in terms of three components (RGB or HSL) or four components (CMYK). For the four component color representation the use of quaternions, with one real and three imaginary components, is natural. By setting one component to zero, quaternions have been used in RGB or HSL representation of colors and color images. In this paper a new quantity, trinion, with one real and two imaginary components, is introduced and its use in color image representation is examined. The goal is to see if significant efficiencies in representation, analysis and computation involving three component color images accrue with the use of trinions. Two versions of the trinion Fourier transform (TFT) are introduced and it is shown that using TFT is preferable for combined analysis of three component color images rather than separate monochromatic analysis of each component and use of quaternions. Joint space-wavenumber localized trinion S (TS) transform with a two-dimensional Gaussian window function that scales with wavenumbers is also presented. Invertibility, rotation invariance, and computational aspects of the TS transform are discussed.     

基于彩色图像的增强算法

本文在分析常用锐化算法的基础上，对其进行改进，提出了一种新的针对彩色图像的边缘增强算法，并用模糊集理论选取阈值去除噪声。实验证明，该算法能有效地突出彩色图像的边缘，与其它算法比较，该算法耗时很少。