Abstract
Extending the dynamic range can present much richer contrasts and physical information from the traditional low dynamic range (LDR) images. To tackle this, we propose a method to generate a high dynamic range image from a single LDR image. In addition, a technique for the matching between the histogram of a high dynamic range (HDR) image and the original image is introduced. To evaluate the results, we utilize the dynamic range for independent image quality assessment. It recognizes the difference in subtle brightness, which is a significant role in the assessment of novel lighting, rendering, and imaging algorithms. The results show that the picture quality is improved, and the contrast is adjusted. The performance comparison with other methods is carried out using the predicted visibility (HDR-VDP-2). Compared to the results obtained from other techniques, our extended HDR images can present a wider dynamic range with a large difference between light and dark areas.
Highlights
With the continuous progress of imaging technologies in recent years, one particular demand is to display the acquired images in high quality to resemble the real scenes [1]
The ordinary low dynamic range (LDR) image with 8 bits per channel is usually insufficient to cover all light attributes of a real scene [2]
To retrieve the hidden information from a single LDR image and create a high-quality perceptual image, we propose a method to generate an high dynamic range (HDR) image from a single LDR image
Summary
With the continuous progress of imaging technologies in recent years, one particular demand is to display the acquired images in high quality to resemble the real scenes [1]. The ordinary low dynamic range (LDR) image with 8 bits per channel is usually insufficient to cover all light attributes of a real scene [2]. To derive the brightness information, researchers and practitioners have examined the transformation between the low and high-intensity dynamic extents to obtain the high dynamic range (HDR) images. This has driven the investigation into generating the HDR content from a single LDR image [3,4]. The high dynamic range imaging techniques are used to overcome some challenging problems in traffic light recognition, lane detection, vehicle, and pedestrian detection at night time for driving assistance [5,6]. The HDR cameras can support more than one channel corresponding to different exposure values to extract the object pattern from a dark background [7]
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