Issues in specifying contrast in building elements for people with a visual disability

BACKGROUND: Standards writers, national and international, have used different contrast calculations to set requirements in building elements for people with visual impairments. On the other hand, they have typically set a single requirement (30%) for specifying the minimum contrast. The systems are not linearly related and 30%means something rather different in each system. OBJECTIVE: To provide a comparison of the various scales in order to illustrate the differences caused by multiple scales with a single compliance value, recommend a single scale for universal adoption and, if a new measure is problematic for implementation, to recommend the most perceptually uniform of the present methods. METHODS: We use the contrast between combinations of 205 paint colours to illustrate the relationships between the measures. We use an internationally accepted scale, with equal perceptual steps, as a “gold standard” to identify the most perceptually uniform measurement scale in the existing methods. RESULTS: We show that Michelson contrast is the most perceptually uniform of the existing measurement scales. We show the contrasts in the proposed method that equate to the various current requirements. CONCLUSIONS: We propose that CIE Metric Lightness could be used as the contrast measure. Alternatively, Michelson contrast is the most perceptually linear of the current measurement scales.

A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite

Geostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily affected by clouds, islands and other factors, which make it difficult to detect the ship targets. This paper proposes a new method for detecting ships moving on the sea surface using GF-4 satellite images. First, the adaptive nonlinear gray stretch (ANGS) method was used to enhance the image and highlight small and dim ship targets. Second, a multi-scale dual-neighbor difference contrast measure (MDDCM) method was designed to enable detection of the position of the candidate ship target. The shape characteristics of each candidate area were analyzed to remove false ship targets. Finally, the joint probability data association (JPDA) method was used for multi-frame data association and tracking. Our results suggest that the proposed method can effectively detect and track moving ship targets in GF-4 satellite optical remote sensing images, with better detection performance than other classical methods.

Adopting Image Integration Techniques to Simulate Satellite Images

Mathematical integration techniques rely on mathematical relationships such as addition, subtraction, division, and subtraction to merge images with different resolutions to achieve the best effect of the merger. In this study, a simulation is adopted to correct the geometric and radiometric distortion of satellite images based on mathematical integration techniques, including Brovey Transform (BT), Color Normalization Transform (CNT), and Multiplicative Model (MM). Also, interpolation methods, namely the nearest neighborhood, Bi-linear, and Bi-cubic were adapted to the images captured by an optical camera. The evaluation of images resulting from the integration process was performed using several types of measures; the first type depends on the determination of quality in the regions of the edges using a contrast measure as well as the number of edges and threshold. The second type is the global one that is based on the parameters of the image region, including the Mean (µ), Standard Deviation (SD), and Signal to Noise Ratio (SNR). The parameters also included the Amount of Information Added (AIA) to the original image, such as those for the total (AIAt) , edges (AIAe), and homogenous (AIAh) regions. The results showed the efficiency of the integration process in the image fusion with different resolutions in one image integrated resolution. The quality measures used were also capable in evaluating the most efficient techniques and determining the accurate information of the resulting image.