Construction of nearshore elevation model using open satellite data

For the tasks considering changes of water level it is required to have a combined (above water and underwater) elevation model. And the highest accuracy requirements are imposed on the parts of the model, which produce the contour lines in the range of the actual water level changes, while the information about the underwater elevation is usually very scarce and rough. In the article we consider the possibility to obtain this part of the elevation model using open high resolution (10 m/pixel) satellite images corresponding to different water levels. Here we describe the technique, which allows us to obtain the subpixel accuracy of the resulting contour lines. And we consider the problems in the quality of the satellite images that the contour lines reveal, and some ways to deal with the problems.

A Novel Method for Laser Peak Detection with Subpixel Accuracy for the Rail Corrugation Measurement

In this article, a new wavelet-based laser peak detection algorithm is proposed having subpixel accuracy. The algorithm provides an accurate and rapid measurement platform for the rail surface corrugation with no need to any image noise elimination. The proposed rail Corrugation Measurement System (CMS) is based on the laser triangulation principle, and the accuracy of such system is mainly affected by the laser peak detection in the captured image. The intensity of each row or column of the image is taken as a 1-D discrete signal. Intensity distribution of a laser stripe in this signal follows a Gaussian pattern contaminated by the white noise. Against usual peak detection algorithms with need to prenoise-filtering process, the proposed method based on the wavelet transform is able to perform these tasks efficiently and robustly. Present wavelet-based methods for the peak detection are at pixel level, but for achieving high accuracy subpixel detection is proposed. Experiments show that the capability of the proposed method for laser peak detection is more accurate and faster than the filter-based methods, especially for low S/N ratios. Also, this technique can be utilized for any application in laser peak detection with subpixel accuracy. A prototype system based on the proposed method for the rail corrugation measurement has been designed and manufactured. Results of the rail corrugation measurement guarantee capability of the proposed methodology for accurate measurement of the rail corrugation and its potential for industrial application.

Advanced sun-sensor processing and design for super-resolution performance

The performance of conventional and parametric super-resolution algorithms for estimating sun position in a spacecraft sun-sensor was analyzed. Widely employed in other applications, parametric algorithms were examined to evaluate increase in system performance without affecting the cost of the sensor system. Using a simplified model of detector illumination simulations provided quantitative comparisons of algorithm performance. Simple sensor re-design was examined by using genetic algorithms as a heuristic to optimize the illumination pattern for a single axis digital sun-sensor. Findings show that, multiple narrow peak patterns provide subpixel accuracy in resolving the sun-angle. The optimal illumination pattern can be implemented by fabricating a replacement aperture mask for the sensor and this change can be made at a minimal cost. The super-resolution algorithms were tested with a component noise model and image degradation due to Earth albedo effects were examined. Parametric algorithms display very good performance throughout the test regime. The improvements are substantial enough to validate this approach worthy of future study.

Advanced sun-sensor processing and design for super-resolution performance

The performance of conventional and parametric super-resolution algorithms for estimating sun position in a spacecraft sun-sensor was analyzed. Widely employed in other applications, parametric algorithms were examined to evaluate increase in system performance without affecting the cost of the sensor system. Using a simplified model of detector illumination simulations provided quantitative comparisons of algorithm performance. Simple sensor re-design was examined by using genetic algorithms as a heuristic to optimize the illumination pattern for a single axis digital sun-sensor. Findings show that, multiple narrow peak patterns provide subpixel accuracy in resolving the sun-angle. The optimal illumination pattern can be implemented by fabricating a replacement aperture mask for the sensor and this change can be made at a minimal cost. The super-resolution algorithms were tested with a component noise model and image degradation due to Earth albedo effects were examined. Parametric algorithms display very good performance throughout the test regime. The improvements are substantial enough to validate this approach worthy of future study.

Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study

Dense image matching is a crucial step in many image processing tasks. Subpixel accuracy and fractional measurement are commonly pursued, considering the image resolution and application requirement, especially in the field of remote sensing. In this study, we conducted a practical analysis and comparative study on area-based dense image matching with subpixel accuracy for remote sensing applications, with a specific focus on the subpixel capability and robustness. Twelve representative matching algorithms with two types of correlation-based similarity measures and seven types of subpixel methods were selected. The existing matching algorithms were compared and evaluated in a simulated experiment using synthetic image pairs with varying amounts of aliasing and two real applications of attitude jitter detection and disparity estimation. The experimental results indicate that there are two types of systematic errors: displacement-dependent errors, depending on the fractional values of displacement, and displacement-independent errors represented as unexpected wave artifacts in this study. In addition, the strengths and limitations of different matching algorithms on the robustness to these two types of systematic errors were investigated and discussed.

Phase correlation functions: FFT vs. FHT

<p><span lang="EN-GB">The ability to process an image is a crucial skill in many measurement activities. In image processing or pattern recognition, Fast Fourier Transform (FFT) is widely used. In particular, the Phase Only Correlation (POC) method demonstrates high robustness and subpixel accuracy in pattern matching. However, there is a disadvantage in the required memory machine because of the calculation of 2D-FFT. In applications in which the use of memory is a critical element, Fast Hartley Transform (FHT) seems to be a good substitute. In this context, the use of Hartley’s transform can be of interest for apps implemented on portable systems e.g. smartphones. In this article, we present a comparison of the implementations of the phase correlation function using FFT and FHT. Particular attention is given to the analytical steps necessary to implement the POC by means of the Hartley transform.</span></p>