Fusion of near-infrared and RGB images on a FPGA using high level synthesis tool
Several applications utilizes a set of Red Green Blue (RGB) and Near Infrared (NIR) images have been emerging over recent years. The present work proposes a technique of enhancing an image by combining colour (RGB) and near infrared information (NIR). In order to fuse the two types of images, the NIR-channel is considered as a luminance counterpart to the visible image. International standard database (RGB-NIR Scene Dataset) is used in this work for image fusion. In this work, the original RGB image is converted into two different colour spaces namely HSV and YCbCr. Here, the luminance channel is replaced with the near infrared channel thereby obtaining a fused enhanced image. RGB-NIR dataset is used in the present work for testing the proposed image fusion algorithm and the quality of the fused image is measured through Peak Signal to Noise Ratio (PSNR). The experimental results indicates that HSV colour space is more efficient in image fusion compared to YCbCr colour space based on PSNR values of different images. Finally, this complete fusion algorithm is implemented on Xilinx Nexys4 FPGA board to be able to obtain real-time outputs in the form of vivid, contrasted images that are pleasing to the observers. The experimental results shows that, the Xilinx FPGA utilizes less memory and less power compared to other fusion algorithms.