Hardware Implementations of Dehazing Algorithms

Haze, a phenomenon arising from the scattering of light by atmospheric particles, imparts undesirable visual artifacts and degradation to images, posing challenges across various applications. This review paper delves into the realm of dehazing algorithms, with a specific focus on their hardware implementations. The introductory section lays the groundwork by elucidating the nature of haze, its diverse types, and the detrimental impacts it inflicts on image quality through light scattering mechanisms. In response to the pressing need for real-time dehazing solutions, the paper navigates through the landscape of hardware-based dehazing algorithms This review addresses the intricate hurdles encountered in translating dehazing algorithms into hardware architectures. These challenges span architectural design considerations, power efficiency optimizations, memory bandwidth management, and algorithmic adaptation for parallel processing. To benchmark the advancements achieved thus far, the paper delves into a comparative analysis of diverse hardware implementations and their corresponding results. Notable architectural choices, from FPGA (Field-Programmable Gate Array) to specialized ASICs (Application-Specific Integrated Circuits) are dissected in terms of their performance metrics, energy efficiency, and suitability for real-time applications. This assessment also encompasses an examination of trade-offs between accuracy and computational speed in various hardware contexts. Drawing insights from the reviewed literature, this paper offers a comprehensive overview of the strides taken in the field of hardware-based dehazing algorithms. The synthesis of challenges, architectures, and comparative results provides a roadmap for future research directions, offering insights into potential areas of improvement and innovation.