īy the combined insect compound eye imaging mechanism with compressed sensing joint sparse model (JSM-1) model, we use the spatial correlation of multiple sampled signals to get the compressive sampling and reconstruction. Currently, the compressed sensing theory and application of the independent-channel signal have been developed in-depth, such as single-pixel camera imaging. According to the compressed sensing theory, the compressive sampling can be executed effectively if there is a corresponding sparse representation space. This method can get the reconstruction results as effectively as the traditional imaging systems do, or even higher quality (in resolution, SNR, etc.), with fewer sensors, lower sampling rate, less data volume, and lower power consumption. Recently, the compressed sensing theory provides a new approach for computer vision, image acquisition, and reconstruction. (b) Adaptation in the view-field of ommatidia and compound eyes. (a) Structure adaptation in ommatidia visual system. Light-dim adaptive regulatory mechanism of ommatidia. For instance, the ommatidia visual field is 5° under dim-adapted pattern, but the corresponding visual field will be only 2° under bright-adapted pattern, and some other species also have similar characteristics. According to Schiff’s research, the imaging angle and visual field of the mantis shrimp ommatidia both change while the light intensity condition changes. Ultimately, the imaging system can reach balance between the visual field and the resolution, as shown in Figure 1. Based on the biological mechanism above, the ommatidia visual field can be narrowed or expanded to get a relatively stable number of incoming photons and a better spatial resolution. Under the light and the dim environment conditions, the mantis shrimp can regulate the length of rhabdome and lens through relaxing or contracting the myofilament. The ommatidia get the different optical information depending on the different lighting conditions. Through the joint action of the lens and the rhabdome, the mantis shrimp has different degrees of overlapping images in the whole region of the ommatidia. To adapt to the changing environment, this species, whose ommatidia structure is fixed, must regulate the light acceptance angle adaptively. In such living environment, the light condition changes dramatically, due to the combined effect of sunlight and water media. Some studies have found that insects have a relatively broad living environment, for instance, the mantis shrimp can live between 50 m and 100 m depth underwater. Interpolation-based reconstruction methods do improve the effect of image reconstruction, but they destroy the high-frequency detailed information of the original image. However, only the correlation between the local and global pixels is considered in these algorithms. These algorithms can improve the reconstruction quality of the original image to some extent. As a compromise, bilinear interpolation is often used for research. Although the reconstruction results of bicubic interpolation are better than the others, they always lose efficiency and take much more time. However, the reconstructed image by bilinear interpolation appears saw-tooth and blurring sometimes.

According to existing research, the reconstruction accuracy of bilinear interpolation is higher than that of the nearest neighbor algorithm, and the former can get better image reconstruction results. The classical reconstruction methods include the nearest neighbor algorithm, bilinear interpolation, and bicubic interpolation algorithm. Furthermore, there is no distinct block effect in the result, and the edge of the reconstructed image is smoother than that obtained by the other two reconstruction methods in this work. The simulation of a four-channel ARM-ICE system shows that the new method improves the peak signal-to-noise ratio (PSNR) and resolution of the reconstructed target scene under two different cases of light intensity. Based on the compressed sensing joint sparse model (JSM-1), we establish an information processing system of ARM-ICE. Meanwhile, ARM-ICE can regulate the visual field of sampling to control imaging according to the environment light intensity. The target scene can be compressive, sampled independently with multichannel through ARM-ICE. Inspired by the mechanism of imaging and adaptation to luminosity in insect compound eyes (ICE), we propose an ICE-based adaptive reconstruction method (ARM-ICE), which can adjust the sampling vision field of image according to the environment light intensity.

Insect eye xsection