Proceedings ArticleDOI
Coloring night-vision imagery with statistical properties of natural colors by using image segmentation and histogram matching
Yufeng Zheng,Bruce C. Hansen,Andrew M. Haun,Edward A. Essock +3 more
- Vol. 5667, pp 107-117
TLDR
In this paper, the mean, standard deviation and histogram distribution of a set of natural scene images are used as the target color properties for each color scheme, and the final grayscale image segments are obtained by using clustering and merging techniques.Abstract:
A natural color mapping method has been previously proposed that matches the statistical properties (mean and standard deviation) of night-vision (NV) imagery to those of a daylight color image (manually selected as the "target" color distribution). Thus the rendered NV image appears to resemble the target image in terms of colors. However, in this prior method the colored NV image may appear unnatural if the target image's "global" color statistics are too different from that of the night vision scene (e.g., it would appear to have too much green if much more foliage was contained in the target image). Consequently, a new "local coloring" method is presented in the current paper, and functions to render the NV image segment-by-segment by using a histogram matching technique. Specifically, a false-color image (source image) is formed by assigning multi-band NV images to three RGB (red, green and blue) channels. A nonlinear diffusion filter is then applied to the false-colored image to reduce the number of colors. The final grayscale image segments are obtained by using clustering and merging techniques. The statistical matching procedure is merged with the histogram matching procedure to assure that the source image more closely resembles the target image with respect to color. Instead of using a single target color image, the mean, standard deviation and histogram distribution of a set of natural scene images are used as the target color properties for each color scheme. Corresponding to the source region segments, the target color schemes are grouped by their scene contents (or colors) such as green plants, roads, ground/earth. In our experiments, five pairs of night-vision images were initially analyzed, and the images that were colored (segment-by-segment) by the proposed "local coloring" method are shown to be much more natural, realistic, and colorful when compared with those produced by the "global-coloring" method.read more
Citations
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Book
Color Appearance Models
TL;DR: This book is a good overview of the most important and relevant literature regarding color appearance models and offers insight into the preferred solutions.
Journal ArticleDOI
Progress in color night vision
TL;DR: A sample-based color transfer method that is specific for different types of materials in a scene and can be easily adapted for the intended operating theatre and the task at hand is presented.
Journal ArticleDOI
Fast natural color mapping for night-time imagery
TL;DR: 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 is presented.
Journal ArticleDOI
Colour Mapping: A Review of Recent Methods, Extensions and Applications
H. Sheikh Faridul,Tania Pouli,Christel Chamaret,Jürgen Stauder,Erik Reinhard,Dmitry Kuzovkin,Alain Trémeau +6 more
TL;DR: A comprehensive overview of colour mapping or colour transfer methods is presented and a classification of current solutions depending not only on their algorithmic formulation but also their range of applications is offered.
Proceedings ArticleDOI
Method for applying daytime colors to nighttime imagery in realtime
TL;DR: In this paper, a fast and efficient method to derive and apply natural colors to nighttime imagery from multiband sensors is presented, which is derived from the combination of a multiband image and a corresponding natural color reference image, and yields a nightvision image with colors similar to that of the daytime image.
References
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