This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.
We study a technique for improving visualization quality of noisy multispectral images. Contrast form visualization approach is considered, which guarantees a non-zero contrast in the output image when there is a difference between the spectra of the object and the background in the input image. The improvement is based on channel weighting according to estimation of the noise level. We show this approach to reduce noise in color visualization of real multispectral images. The low-noise visualizations are demonstrated to be more comprehensive to a human on examples from a publicly available dataset of Earth surface images. Noise variance estimation needed for weighting uses the method proposed earlier by the authors. The validation dataset consists of publicly available images of Earth surface.
In this paper we study multiple reflection effect in a fold of material with regard to color constancy problem. Namely we consider light source chromaticity estimation using perceived material color. We measured relative spectra of reflected light source emission for different positions under folds. Experiment was performed on 105 fabric samples. Using this data we discuss applicability of different spectral models for description of observed chromaticity deviation in different fold’s areas. Obtained experimental data was released in open access.
In this paper we propose a novel method for localization based on matching two stereo images. It is based on minimizing the sum of square distances between each 3D point and four corresponding 3D rays. The method shows good results for practical localization purposes. Moreover it is robust to the presence of feature point correspondences with zero disparity, which is usually a problem for classical methods. The algorithm is tested in comparison to the classical method. It has linear complexity with respect to feature point correspondence number.
This paper presents a method of radial distortion automatic compensation on video from an unknown camera. The proposed algorithm estimates the distortion parameters by analyzing a sequence of video frames. It does not require any calibration objects, but is based on the assumption that the original scene contained straight lines. The method tries to perform such radial distortion correction that makes lines look generally straighter. To estimate the overall curvature of the lines we propose to use the fast Hough transform; without actually detecting them in the image. The proposed algorithm has been tested on real data.
We describe a fast method for road detection in images from a vehicle cabin camera. Straight section of roadway is detected using Fast Hough Transform and the method of dynamic programming. We assume that location of horizon line in the image and the road pattern are known. The developed method is fast enough to detect the roadway on each frame of the video stream in real time and may be further accelerated by the use of tracking.
Demosaicing is the process of reconstruction of a full-color image from Bayer mosaic, which is used in digital cameras for image formation. This problem is usually considered as an interpolation problem. In this paper, we propose to consider the demosaicing problem as a problem of solving an underdetermined system of algebraic equations using regularization methods. We consider regularization with standard l1/2-, l1 -, l2- norms and their effect on quality image reconstruction. The experimental results showed that the proposed technique can both be used in existing methods and become the base for new ones