Abstract
Hardware suitability of an algorithm can only be verified when the algorithm is actually implemented in the hardware. By hardware, we indicate system on chip (SoC) where both processor and field-programmable gate array (FPGA) are available. Our goal is to develop a simple algorithm that can be implemented on hardware where high-level synthesis (HLS) will reduce the tiresome work of manual hardware description language (HDL) optimization. We propose an algorithm to achieve high dynamic range (HDR) image from a single low dynamic range (LDR) image. We use highlight removal technique for this purpose. Our target is to develop parameter free simple algorithm that can be easily implemented on hardware. For this purpose, we use statistical information of the image. While software development is verified with state of the art, the HLS approach confirms that the proposed algorithm is implementable to hardware. The performance of the algorithm is measured using four no-reference metrics. According to the measurement of the structural similarity (SSIM) index metric and peak signal-to-noise ratio (PSNR), hardware simulated output is at least 98.87 percent and 39.90 dB similar to the software simulated output. Our approach is novel and effective in the development of hardware implementable HDR algorithm from a single LDR image using the HLS tool.
Highlights
Vision is one of the most important senses
When we talk about modern science, the camera is an instrument that is analogous to eyes but the capability of eyes is far better than the camera
At the time of this implementation, we have found that, during the use of comparator operator (>/
Summary
Vision is one of the most important senses. The things observed by us are analyzed by the brain to help us in taking decision. When we talk about modern science, the camera is an instrument that is analogous to eyes but the capability of eyes is far better than the camera. A camera can capture a moment through an image or video and store it. Camera by itself cannot take a decision and, for that purpose, camera needs a system similar to the human brain to analyze the data. A field-programmable gate array (FPGA) can be used in a camera as a real-time system to analyze the captured image. The language for FPGA is related to the way of resource implementation in the FPGA
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