Measurement of 3D scene from image sequences is necessary for many computer vision applications. In this paper, we identify the volumetric scene reconstruction as a critical issue for target measurement and use the statistical method to estimate the size of the reconstructed target. The proposed approach unifies the view volume in volumetric scene reconstruction while we only know the location information of the camera relative to the target in elliptical orbit. Experimental results on elliptical orbit with 200 meters long axis and 100 meters short axis illustrate that the average error is about 44 millimeters, which meets the accuracy requirement of general measurement.
The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.
Gamma correction is a necessary operation for a digital image before it is sent to display. Uneven illumination images have low resolution and a lot of information is covered. In order to better removal of light effects and reproduce truly plain circumstances, this paper presents a new local adaptive gamma correction method. The experiment shows this method makes the brightness distribution more uniform and proved that the method compared with other methods that have better correction results.
Radiometric calibration is an important part for space remote sensing camera to obtain an accurate radiation value of ground target. The main significance of radiometric calibration is to reduce the influence by external scene and internal parameters of camera and to recover the real radiation property of objects. In order to break the limitation of line array imaging sensor, we propose a radiometric calibration method based on camera state matrix for area array camera. According to camera response characteristics, calculate and fit a functional relationship between the input radiance energy and the output digital number. Meanwhile, analyse and describe the procedure of radiometric calibration in detail. Experimental results indicates that the calibration method can provide high accuracy linear fitting parameters and can be widely applied to a large variety digital imaging systems.
Proc. SPIE. 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015)
KEYWORDS: Chromatic aberrations, Light sources, Image processing, Reflectivity, Image restoration, Image analysis, Light sources and illumination, Machine vision, Human vision and color perception, RGB color model
Color constancy is an important problem in machine vision and image processing ﬁelds. We propose a new method in this paper that is based on detail information description to estimate the chromaticity of the light source and restore the real color property of captured images. The main idea of the proposed approach is that according to human vision characteristics use the interest information in an image to estimate the lighting condition of real scene. To approve the proposed method, two well-known algorithms are selected and their contrast results are also presented. It is shown in this paper that the proposed approach performs better than other traditional methods for color constancy most of the time.
Camera calibration is one of the essential steps in the computer vision research. This paper describes a real-time OpenCV based camera calibration system, and developed and implemented in the VS2008 environment. Experimental results prove that the system to achieve a simple and fast camera calibration, compared with MATLAB, higher precision and does not need manual intervention, and can be widely used in various computer vision system.
Color constancy performs an important role in computer vision and digital color image processing. The traditional color regulation algorithms which are based on the gray world assumption neglect the correlation between the three stimulus color components and the nonlinear effect between the different gray levels. In this paper, we propose a novel color constancy algorithm which is based on gray-curve regulation. The proposed algorithm first divides the luminance interval into several parts and then regulates the gray-curves of RGB three channels in each subinterval which can solve the correlation and nonlinear problems simultaneously. The experiment results show the effectiveness of the proposed algorithm.