Multispectral Transmission Map Fusion Method and Architecture for Image Dehazing
Rahul Kumar, Brajesh Kumar Kaushik, Ravi Balasubramanian · IEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2019
Image dehazing is an essential preprocessing stage for several applications such as surveillance, long-range imaging, automatic driver-assistance system (ADAS), and remote sensing. Haze particles degrade visible-band images more severely than the infrared images due to scattering phenomena. Therefore, infrared data can be effectively utilized to enhance the visibility of color images captured in a hazy environment. In this brief, for the first time, a multispectral transmission map fusion approach is presented, wherein a haze-aware weight generation scheme is used to improve transmission map in specific regions. This achieves significant quantitative improvement as compared with the existing methods. In addition, the method is extremely suitable for hardware implementation. Therefore, a low-cost very large-scale integration (VLSI) architecture is also presented. The application-specified integrated circuit (ASIC) and field-programmable gate array (FPGA) implementations dissipate 3.45- and 57-mW power at 150 MHz, respectively. Both ASIC and FPGA achieve a high throughput of 450 and 308 Mpixels/s, respectively. The design does not require any external memory such as dynamic random access memory, thus making it suitable for on-chip processing that can be closely integrated with an image sensor.