Field Programmable Gate Arrays Implementation of Two-Point Non-Uniformity Correction and Bad Pixel Replacement Algorithms

Njuguna, Josphat Chege; Alabay, Emre; Çelebi, Anıl; Güllü, M. Kemal

doi:10.1109/inista52262.2021.9548499

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…Our design, in comparison to [ 18 ], encompasses a greater range of functionalities for infrared image processing. The designs [ 19 , 20 ] are similar to our design approach. The functions of NUC and blind pixel compensation are integrated in [ 19 ].…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…The designs [ 19 , 20 ] are similar to our design approach. The functions of NUC and blind pixel compensation are integrated in [ 19 ]. For [ 20 ], several functions such as geometric transformation, lens distortion correction, and image registration are included.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…As our design marks the first application of SWF in the field of infrared image processing, its edge-preserving effect allows our algorithm to retain edge information while handling noise. Compared to [ 19 , 20 ], our approach not only eliminates noise but also preserves image clarity to a greater extent. Additionally, in our design, histogram equalization is applied before image output.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…The architecture was implemented on XC6SLX45T with a resolution of

14-bit pixels at up to 238 FPS with low resource utilization and adds only 13 mW to the FPGA power. Njuguna [ 19 ] proposed an FPGA architecture for two-point non-uniformity correction and bad pixel replacement. The design realizes a maximum operating frequency of 300 MHz and consumes 4293 look-up tables (LUTs), 4261 flip-flops, 11 digital signal-processing blocks, and five block random access memories.…”

Section: Introductionmentioning

confidence: 99%

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Lightweight and Real-Time Infrared Image Processor Based on FPGA

Wang,

He,

Zhu

et al. 2024

Sensors

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This paper presents an FPGA-based lightweight and real-time infrared image processor based on a series of hardware-oriented lightweight algorithms. The two-point correction algorithm based on blackbody radiation is introduced to calibrate the non-uniformity of the sensor. With precomputed gain and offset matrices, the design can achieve real-time non-uniformity correction with a resolution of 640×480. The blind pixel detection algorithm employs the first-level approximation to simplify multiple iterative computations. The blind pixel compensation algorithm in our design is constructed on the side-window-filtering method. The results of eight convolution kernels for side windows are computed simultaneously to improve the processing speed. Due to the proposed side-window-filtering-based blind pixel compensation algorithm, blind pixels can be effectively compensated while details in the image are preserved. Before image output, we also incorporated lightweight histogram equalization to make the processed image more easily observable to the human eyes. The proposed lightweight infrared image processor is implemented on Xilinx XC7A100T-2. Our proposed lightweight infrared image processor costs 10,894 LUTs, 9367 FFs, 4 BRAMs, and 5 DSP48. Under a 50 MHz clock, the processor achieves a speed of 30 frames per second at the cost of 1800 mW. The maximum operating frequency of our proposed processor can reach 186 MHz. Compared with existing similar works, our proposed infrared image processor incurs minimal resource overhead and has lower power consumption.

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