Toward a single-pixel near-infrared low-resolution 2D image reconstruction strategy

In this article, we propose a method to be used for the reconstruction of single-pixel near-infrared (SPI-NIR) low-resolution 2D images using active illumination with a peak wavelength on 1550 nm, that is based on Batch Orthogonal Matching (Batch-OMP) processing algorithms and a region definition in the projection sequence of Hadamard illumination patterns using the Genetic algorithm (GA). Different methods to generate Hadamard pattern sequences have been reported, mostly based on switching the illumination sequence on and off to improve the quality of the reconstructed image, thereby increasing the Structural Similarity Index Measure (SSIM) level and reducing the processing time. These methods are efficient for image sizes of $> 64\times 64$ virtual pixels, but for lower resolutions with small coherence areas $A_{ch}$, the SNR level of the reconstructed image is very low, which makes other methods, such as those using the Zig-Zag or Hilbert filling curves for the scanning path, an option for the reconstruction of SPI-NIR low-resolution images. Due to the fact that in the present application, we deal with low-resolution (size image $8\times 4$ virtual pixels) SPI-NIR images, we present a solution to improve the obtained image quality (aiming at $\text{PSNR} > 10dB$ and $\text{SSIM} > 0.5$) that is based on the use of a specific scanning path and a combination of a genetic algorithm to define the switching sequences of the Hadamard patterns, using Batch-OMP algorithm for image reconstruction, in the processing time range between 20 and 35 ms.