Natural Day-time Color Appearance Research Articles

A Novel Color Image Fusion for Multi Sensor Night Vision Images

In this paper presents a simple and fast color fusion approach for night vision images. Image fusion involves merging of two or more images in such a way, to get the most advantageous characteristics of each image. Here the Visible image is fused with the InfraRed (IR) image, so the desired result will be single, highly informative image providing full information. This paper focuses on color constancy and color contrast problem. Firstly the contrast of the infrared and visible image is enhanced using Local Histogram Equation. Then the two enhanced images are fused in three compounds of a LAB image using aDWT image fusion. This paper adopts an approach which transfer color from the reference image to the fused image using Color Transfer Technology. To enhance the contrast between the target and the background, a scaling factor is introduced in the transferring equation in the b channel. Finally our approach gives the Multiband Fused image with the natural day-time color appearance and the hot targets are popped out with intense colors while the background details present with the natural color appearance.

Fast color contrast enhancement method for color night vision

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in color image fusion, resulting in a plethora of pixel-level image fusion algorithms. In this study a simple and fast fusion approach for color night vision is presented. The contrast of infrared and visible images is adjusted by local histogram equalization. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To obtain false color images possessing a natural day-time color appearance, this paper adopts an approach which transfers color from the reference to the fused images in a simplified Lab space. To enhance the contrast between the target and the background, a stretch factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot targets are popped out with intense colors while the background details present natural color appearance. Target detection experiments also show that the presented method has a better performance than the former methods, owing to the target recognition area, detection rate, color distance and running time.

One color contrast enhanced infrared and visible image fusion method

Color constancy (Toet and Franken, 2003 [2]; Toet, 2003 [7]) and color contrast (Scribner et al., 2000 [21]; Lee et al., 2005 [23]) are two important topics for color image fusion. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Color transfer technology is popular in infrared (IR) and visible image fusion to give the fused image a natural day-time color appearance (Toet, 2003 [7]; Wang et al., 2007 [8]; Zheng and Essock, 2008 [9]). However, in the color transfer step, all three channels of the color space are processed with the same linear mapping without color enhancement, resulting in low color contrast between the target and the background (Wang et al., 2007 [8]). Based on the characteristics of the IR image, we introduce a ratio of local to global divergence of the IR image to improve the color contrast. The enhancement ratios for both hot and cold targets are larger than one, while it tends to one for the background. As a result, the proposed method pops out both hot and cold targets in color, where hot targets will appear intense red, and cold targets will appear cyan. Subjective results show visible color contrast enhancement effects. Target detection experiments through hue and saturation components of the fused image show an improvement in the hit rate for target detection, owing to larger color distance between the target and the background.

Fast natural color mapping for night-time imagery

We present a new method to render multi-band night-time imagery (images from sensors whose sensitive range does not necessarily coincide with the visual part of the electromagnetic spectrum, e.g. image intensifiers, thermal camera’s) in natural daytime colors. The color mapping is derived from the combination of a multi-band image and a corresponding natural color daytime reference image. The mapping optimizes the match between the multi-band image and the reference image, and yields a nightvision image with a natural daytime color appearance. The lookup-table based mapping procedure is extremely simple and fast and provides object color constancy. Once it has been derived the color mapping can be deployed in real-time to different multi-band image sequences of similar scenes. Displaying night-time imagery in natural colors may help human observers to process this type of imagery faster and better, thereby improving situational awareness and reducing detection and recognition times.

Fusion of visible and infrared imagery for night color vision

A combined approach for fusing night-time infrared with visible imagery is presented in this paper. Night color vision is thus accomplished and the final scene has a natural day-time color appearance. Fusion is based either on non-negative matrix factorization or on a transformation that takes into consideration perceptual attributes. The final obtained color images possess a natural day-time color appearance due to the application of a color transfer technique. In this way inappropriate color mappings are avoided and the overall discrimination capabilities are enhanced. Two different data sets are employed and the experimental results establish the overall method as being efficient, compact and perceptually meaningful.

Colorizing single band intensified nightvision images

We present a method to give single band intensified nightvision imagery a natural day-time color appearance. For input, the method requires a true color RGB source image and a grayscale nightvision target image. The source and target image are both transformed into a perceptually decorrelated color space. In this color space a best matching source pixel is determined for each pixel of the target image. The matching criterion uses the first order statistics of the luminance distribution in a small window around the source and target pixels. Once a best matching source pixel is found, its chromaticity values are assigned (transferred) to the target pixel while the original luminance value of the target pixel is retained. The only requirement of the method is that the compositions of the source and target scenes resemble each other.