Color Distortion Problem Research Articles

一种利用大气散射模型实现图像去雾的方法

针对雾天图像清晰度不高的问题，我们采用大气散射模型进行图像去雾处理，利用Curvelet变换提取图像边缘，根据边缘相交的直线先计算灭点值，再由灭点计算景深值，得到含雾图像中入射光的辐射系数，即图像真实的颜色值，达到图像去雾的目的。在景深值计算中，分别对含雾图像的每个像素点都做一次景深计算，在一定程度上可以解决由于单一景深导致部分区域颜色失真的问题，使去雾后图像的颜色更自然。最后，通过实验验证了方法的有效性。 In view of the problem that the image under foggy days is not clear, the atmospheric scattering model is used to process the image dehazing. First, the Curvelet transform extracts the image edge and calculates the vanishing point on the basis of the intersection of straight line edges. Then it calculates the depth of field value according to the vanishing point. The radiation coefficient of incident light in the foggy image is obtained, which means that the real color value of the image is obtained and the image dehazing is finished. When calculating the depth of field value, it respectively calculates the depth of field value of every foggy image’s pixel at the same time, which solves the partial area color distortion problem that is caused by using single depth of field, and makes the processed image look more natural. Finally, the validity of the method is verified by experiments.

Single image haze removal based on haze physical characteristics and adaptive sky region detection

Outdoor images are often degraded by haze and other inclement weather conditions, which affect both consumer photographs and computer vision applications severely. Therefore, researchers have proposed plenty of restoration approaches to deal with this problem. However, it is hard to tackle the color distortion problem in restored images with ignoring the differences between fog and haze. Meanwhile, the atmospheric light is also an important variable that influences the global illumination of images. In this paper, we analyze the physical meaning of atmospheric light first, and estimate atmospheric light by a novel method of obtaining the sky region in images, which is based on our newly proposed sky region prior. Then after exploring physical characteristics of fog and haze, we explain why images taken in haze appear yellowish, and eliminate this phenomenon by our adaptive channel equalization method. Quantitative comparisons with seven state-of-art algorithms on a variety of real-world haze images demonstrate that our algorithm can remove haze effectively and keep color fidelity better.

Spatial Injection to Low Resolution Images using IIHS Transform

Image fusion, the process of combining multi-modal or multi-focus images to form a new informative image than input images. The fused image contains more information than their input images which helps remote sensing applications for image analysis efficiently. Many image fusion algorithms have been developed, but all of them introduced a term called as color distortion. The huge difference between the intensity of input images leads to the color distortion. The Intensity-Hue-Saturation fusion technique gives more access to the user to work on pixel by pixel. This method accessibility delivers the good fusion technique base to reduce the color distortion. We proposed an algorithm which solves the color distortion problem effectively and it can produce an output image as highly informative. The difference in intensity of input images reduced by injecting the intensity of the high resolution image. The proposed work performs better than existing algorithms and it is proved by statistical measures like a correlation coefficient, mean, standard deviation, ERGAS, UIQI and spectral angle mapper.

인간 시각 인지에 기반을 둔 높은 동적폭을 갖는 영상 보정 방법

For last several decades, the color correction methods have been proposed for HDR(high dynamic range) images. However, color distortion problems take place after correcting the colors such as halos, dominant color as well known. Accordingly, this article presents a novel approach in which the method consists of tone-mapping method and cone response function. In the proposed method, the tone mapping method is used to improve the contrast in the given HDR image based on chromatic and achromatic based on the CIEXYZ tristimulus value, expressed in c/m. The cone response function is used to deal with mismatch between corrected image and displayed image as well as to estimate various human visual effects based on the CMCAT2000 color appearance model. The experimental results show that the proposed method yields better performance of color correction over the conventional method in subjective and quantitative quality, and color reproduction.

Reconstruction of three-dimensional flame with color temperature

The reconstruction of flame from the captured images is a difficult and computationally expensive problem. Reconstruction from color images will keep the colorful appearance, as is beneficial for visually realistic flame modeling. Most of existing color-image-based methods rebuild three density fields from RGB intensities; however, these methods suffer from the color distortion problem due to the high correlation of RGB intensities. A novel method for 3D flame reconstruction using color temperature is presented in this paper. Color-temperature mapping is calculated to avoid color distortion; this method maps the RGB intensities into the color temperature and its joint intensity. We improve the multiplication reconstruction with visual hull restriction so that the energy distribution is more reasonable, which allows avoidance of the impossible zones. Experimental results indicate that our approach is efficient in the visually plausible 3D flame generation and produces better color restorations.

A Robust Image Fusion Method Based on Local Spectral and Spatial Correlation

To solve the potential color distortion problem of synthetic-variable-ratio method, an improved fusion method based on local spectral and spatial correlation (SSC) is presented. The proposed method, which uses SSC characteristics and local optimization strategy to simulate a low-resolution panchromatic image, can effectively reduce the spectral distortion of the fused image. QuickBird and other satellite images are used to assess the quality of the method. Visual and quantitative analysis demonstrates that the proposed approach can significantly improve the fusion quality.

马尔科夫随机场模型下的Retinex夜间彩色图像增强

As Retinex algorithm usually has the problems of halo artifacts,color distortion,high noises and poor details in a low-illumination night color image,this paper proposes a novel Retinex enhancement algorithm based on Markov Random Fields(MRF)to enhance the visibility of single image. This algorithm uses the linear guided filter to estimate image illumination component in HSV(Hue Saturation Value)color space.The reflection image can be obtained through MRF model,and the night color image can be enhanced after color restoration and brightness correction.Compared with the original images,the experimental results demonstrate that the mean value(luminance)of image restored by proposed method has increased more than 2times,and the evaluation indexes such as standard deviation,entropy,the Peak Signal and Noise Ratio(PSNR)and so on have increased more than 5%.Compared with other Retinex algorithms,the effect of enhancement of this algorithm is more remarkable in halo effect elimination,noise suppression and detail preservation.

Study on Detection and Localization Algorithm of Traffic Signs from Natural Scenes

Automatic detection and location of traffic signs is an important part of intelligent transportation, especially for unmanned vehicle technology research. For the morphological feature of China road traffic signs, we propose a traffic sign detection method based on color segmentation and shape analysis. Firstly, in order to solve the problems of traffic signs color cast, distortion, and cross-color in natural scenes, the images are processed by white balance, Retinex color enhancement, and affine transformation. Then, the type of traffic signs is discriminated and detected, according to the color and shape characteristics of traffic signs. The experimental results show that this method can effectively detect and recognize traffic signs.

A New Developed GIHS-BT-SFIM Fusion Method Based On Edge and Class Data

Abstract. The objective of image fusion (or sometimes pan sharpening) is to produce a single image containing the best aspects of the source images. Some desirable aspects are high spatial resolution and high spectral resolution. With the development of space borne imaging sensors, a unified image fusion approach suitable for all employed imaging sources becomes necessary. Among various image fusion methods, intensity-hue-saturation (IHS) and Brovey Transforms (BT) can quickly merge huge amounts of imagery. However they often face color distortion problems with fused images. The SFIM fusion is one of the most frequently employed approaches in practice to control the tradeoff between the spatial and spectral information. In addition it preserves more spectral information but suffer more spatial information loss. Its effectiveness is heavily depends on the filter design. In this work, two modifications were tested to improve the spectral quality of the images and also investigating class-based fusion results. First, a Generalized Intensity-Hue-Saturation (GIHS), Brovey Transform (BT) and smoothing-filter based intensity modulation (SFIM) approach was implemented. This kind of algorithm has shown computational advantages among other fusion methods like wavelet, and can be extended to different number of bands as in literature discussed. The used IHS-BT-SFIM algorithm incorporates IHS, IHS-BT, BT, BT-SFIM and SFIM methods by two adjustable parameters. Second, a method was proposed to plus edge information in previous GIHS_BT_SFIM and edge enhancement by panchromatic image. Adding panchromatic data to images had no much improvement. Third, an edge adaptive GIHS_BT_SFIM was proposed to enforce fidelity away from the edges. Using MS image off edges has shown spectral improvement in some fusion methods. Fourth, a class based fusion was tested, which tests different coefficients for each method due to its class. The best parameters for vegetated areas was k1 = 0.6, k2 = 0.8; and for urban region it was k1 = 0.4, k2 = 0.4. Results might be useful for future studies on fusion methods and their generalization.

Color Distortion of Digital Image and its Detection

To solve the problem of color distortion in the communication and reproduction process, the paper firstly analyzes the causes of the color distortion phenomenon. Then, the paper proposes the corresponding image color distortion detection algorithm based on the HSI color model. In the proposed method, the color image is transformed from RGB space to HSI space firstly; in HSI space, the reference image and the distortion image’s hue differences and saturation differences are calculated. Experimental results on LIVE images show that the measured results of the model with subjective scoring after the nonlinear fit the correlation coefficient up to 0.95 . DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3080

Overcoming “white balance” color distortion problems

1. Michael Beehner, MD <!-- --> 1. Saratoga Springs, New York, USA Around five years ago I reluctantly switched from my beloved film camera to a new Nikon D90 digital camera. I obviously appreciated the ability to pick out the best photos and delete the others, along with the associated cost

Image Fusion Using the Ehlers Spectral Characteristics Preservation Algorithm

Image fusion is a technique that is used to combine the spatial structure of a high-resolution panchromatic image with the spectral information of a low- resolution multispectral image to produce a high-resolution multispectral image. Currently, image fusion techniques via color or statistical transforms such as the Intensity-Hue-Saturation (IHS) and principal component (PC) methods are still widely used. These methods create multispectral images of higher spatial resolution but usually at the cost of color distortions in the fused images. This is especially true if the wavelength range of the panchromatic image does not correspond to that of the employed multispectral bands or for multitemporal/multisensoral fusion. To overcome the color distortion problem, a number of new fusion methods have been developed over the last years. One of these is the Ehlers fusion algorithm, which is based on an IHS transform coupled with adaptive filtering in the Fourier domain. This method preserves the spectral characteristics of the lower spatial resolution multispectral images for single-sensor, multi-sensor, and multi-temporal fusion. A comparison between this method and three sophisticated new fusion techniques that are available in commercial image processing software is presented in this paper using multitemporal multi-sensor fusion with SPOT multispectral and Ikonos panchromatic datasets as well as single-sensor single-date multispectral and panchromatic Quick-bird data. The fused images are compared visually and with statistical methods that are objective, reproducible, and quantitative. It can be shown that the sophisticated methods such as Gram Schmidt fusion, CN spectral sharpening, and the modified IHS provide good results in color preservation for single sensor fusion. For multi-temporal multi-sensor fusion, however, these methods produce significant changes in spectral characteristics for the fused datasets. This is not the case for the Ehlers fusion algorithm, which shows no recognizable color distortion even for multi-temporal and multi-sensor datasets.

Approach to maximize increased details and minimize color distortion for IKONOS and QuickBird image fusion

Both IKONOS and QuickBird offer 11-bit panchromatic and multispectral data in which more details can be extracted from scenes that are very dark under shadows or very washed out due to excessive sun reflectance. In this work, a discrete cosine transform (DCT)-based single-scale Retinex (SSR) technique is presented to extract the highest possible spatial details from the panchromatic image, and a minimum/maximum percent cutoff approach is used to preserve the most spectral information in the multispectral imagery. By fusing those two images, the typical bright target recovery (BTR) response can be avoided. Furthermore, to address the color distortion problem by the fusion process, a fast intensity hue saturation (IHS) image fusion technique with direct saturation stretching in RGB space is also proposed. To verify the efficacy of the proposed techniques, experiments are conducted using real IKONOS and QuickBird imagery covering different areas. Experimental results have shown that the perfect performance, maximizing increased details and minimizing color distortion, is achieved.

A new look at IHS-like image fusion methods

The intensity-hue-saturation (IHS) method, principal component analysis (PCA), Brovey transform (BT) and wavelet transform (WT) are the contemporary image fusion methods in remote sensing community. However, they often face color distortion problems with fused images. In other words, they are sensitive to the characteristics of the analyzed area. To investigate this color distortion problem, this work presents a relatively detailed study indicating that the color distortion problem arises from the change of the saturation during the fusion process. Meanwhile, PCA, BT, and WT are evaluated and found to be IHS-like image merging techniques. Experimental results for distinct image fusion methods are also demonstrated in this paper.

Efficient intensity-hue-saturation-based image fusion with saturation compensation

The intensity-hue-saturation (IHS) and Brovey transforms are two widespread image fusion methods in the remote sensing community. However, both are sensitive to the characteristics of the analyzed area. Restated, they often face color distortion problems with fused images. This work investigates models representing the color space in images. Schemes governing saturation change during fusion are also evaluated to derive the correct saturation values for each pixel in a fused image. In addition, algorithms that compensate distorted saturation values for dis- tinct image fusion methods are derived and discussed. Methods to ex- tend current image fusion methods to any arbitrary order are also out- lined. Finally, an illustrative example of a fused SPOT image demonstrates the color distortion problem while an IKONOS image is adopted to evaluate various contemporary image fusion methods. © 2001 Society of Photo-Optical Instrumentation Engineers. (DOI: 10.1117/1.1355956) Subject terms: image fusion; intensity-hue-saturation (IHS); Brovey transform; IHS with saturation compensation.

Close-Up Photography of Archaeological Objects

The authors review methods of increasing magnification, uses of light boxes and backlighting, ways to photograph flat surfaces of irregular objects, techniques to avoid specular reflections on small objects, approaches to photographing objects close-up with flash, and use of scanning light photomicrography to maintain focus with high magnification. Problems of color distortion in close-up photography are also addressed.