scholarly journals Hyperspectral Imaging Bioinspired by Chromatic Blur Vision in Color Blind Animals

Photonics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 91
Author(s):  
Shuyue Zhan ◽  
Weiwen Zhou ◽  
Xu Ma ◽  
Hui Huang
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging System ◽  
Light Flux ◽  
Image Sensor ◽  
High Light ◽  
Detection Sensitivity ◽  
Imaging Method ◽  
Inverse Filtering ◽  
Color Blind ◽  
Blurred Images

Hyperspectral imaging remote sensing is mutually restricted in terms of spatial and spectral resolutions, signal-to-noise ratio and exposure time. To deal with this trade-off properly, it is beneficial for imaging systems to have high light flux. In this paper, we put forward a novel hyperspectral imaging method with high light flux bioinspired by chromatic blur vision in color blind animals. We designed a camera lens with high degree of longitudinal chromatic aberration, a monochrome image sensor captured the chromatic blur images at different focal lengths. Finally, by using the known point spread functions of the chromatic blur imaging system, we process these chromatically blurred images by deconvolution based on singular value decomposition inverse filtering, and the spectral images of a target were restored. We constructed three different targets for validating image restoration based on a typical octopus eyeball imaging system. The results show that the proposed imaging method can effectively extract spectral images from the chromatically blurred images. This study can facilitate development of a novel bionic hyperspectral imaging, which may benefit from the high light flux of a large aperture and provide higher detection sensitivity.

scholarly journals Optical Aberration Calibration and Correction of Photographic System Based on Wavefront Coding

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4011
Author(s):  
Chuanwei Yao ◽  
Yibing Shen
Keyword(s):  
Imaging System ◽  
Optical Design ◽  
Computational Imaging ◽  
Large Field ◽  
Wavefront Aberration ◽  
Imaging Method ◽  
Image Deconvolution ◽  
Pupil Function ◽  
Wavefront Coding ◽  
Blurred Images

The image deconvolution technique can recover potential sharp images from blurred images affected by aberrations. Obtaining the point spread function (PSF) of the imaging system accurately is a prerequisite for robust deconvolution. In this paper, a computational imaging method based on wavefront coding is proposed to reconstruct the wavefront aberration of a photographic system. Firstly, a group of images affected by local aberration is obtained by applying wavefront coding on the optical system’s spectral plane. Then, the PSF is recovered accurately by pupil function synthesis, and finally, the aberration-affected images are recovered by image deconvolution. After aberration correction, the image’s coefficient of variation and mean relative deviation are improved by 60% and 30%, respectively, and the image can reach the limit of resolution of the sensor, as proved by the resolution test board. Meanwhile, the method’s robust anti-noise capability is confirmed through simulation experiments. Through the conversion of the complexity of optical design to a post-processing algorithm, this method offers an economical and efficient strategy for obtaining high-resolution and high-quality images using a simple large-field lens.

scholarly journals ANALISA CITRA HIPERSPEKTRAL DAUN DARI TANAMAN KELAPA SAWIT YANG MENGALAMI KEKURANGAN AIR MENGGUNAKAN PROGRAM MATLAB

2019 ◽  
Vol 16 (2) ◽  
pp. 143
Author(s):  
JR Lessy Eka Putri ◽  
Minarni Minarni ◽  
Feri Candra ◽  
Herman Herman
Keyword(s):  
Image Processing ◽  
Hyperspectral Imaging ◽  
Oil Palm ◽  
Imaging System ◽  
Water Volume ◽  
Imaging Method ◽  
Pixel Size ◽  
Water Deficiency ◽  
Image Recording ◽  
Detached Leaves

The hyperspectral imaging method has been widely and intensively used in agriculture to find out various problems that occur in plants. Image processing is very important step in an imaging method. This research aims to create Matlab based program to be used to analyze the leaf image of oil palm plants that has experienced water deficiency. Reflectance intensity values were extracted from the process. The hyperspectral imaging system consisted of a 650 nm diode laser, a spectrograph, monochrome CMOS camera, and Matlab image processing program. The samplesused were 8 month old Tenera variety of oil palm seedlings which were treated to simulate water deficiency in the form of variations in the volume of water, namely 0 mL (without watering), 1000 mL, 2000 mL, and 3000 mL (normal), 3 duplicates for each volume. The samples were given water volume of 1000 mL and 2000 mL for every 7 days in 21 days, while the sampleswith 3000 mL of water were watered every day. Image recording was done on the 21st day for detached leaves at the the bottom part.The results showed that the Matlab program was able to separate each row from 15 images, each of which had a pixel size of 1280 × 1024 and merge each of the same lines into 1024 images with a pixel size of 1280 × 15. The reflectance intensity values were then obtained. The results showed that higher levels of water deficiency in plants produce increasing reflectance intensity values.

scholarly journals Smooth Surface Visual Imaging Method for Eliminating High Reflection Disturbance

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4953
Author(s):  
Wei Shao ◽  
Kaibin Liu ◽  
Yunqiu Shao ◽  
Awei Zhou
Keyword(s):  
Surface Defects ◽  
Imaging System ◽  
High Light ◽  
Light Reflection ◽  
Imaging Method ◽  
Charge Coupled Device ◽  
Time Modulation ◽  
Time Space ◽  
Illumination Method ◽  
Visual Imaging

At present, visual imaging is widely applied for surface defects such as bumps and scratches in the manufacture of precise parts with a highly reflective surface. However, the high light reflection and halo disturbance as a result of the illumination in visual imaging exert a direct influence on the accuracy of defect detection. In this regard, the present paper develops an adaptive illumination method based on space–time modulation for a visual imaging system. Furthermore, a digital micro-mirror device (DMD) is employed to realize the pixel-level spatiotemporal modulation of illumination. Then, in combination with the illumination intensity feedback of charge coupled device (CCD), the time-space ratio is adjusted automatically to achieve adaptive uniform illumination and effectively suppress the high light reflection and halo disturbance of highly reflective surfaces. The experimental results show that, in terms of restraining high light disturbance, the visibility and accuracy of visual imaging are improved.

scholarly journals Pencitraan Hiperspekral untuk Membedakan Asal Tanah Tumbuh Dari Tandan Buah Segar Kelapa Sawit

2020 ◽  
Vol 4 (3) ◽  
pp. 761
Author(s):  
Dina Veranita ◽  
Minarni Minarni ◽  
Feri Candra ◽  
Saktioto Saktioto ◽  
Mohammad Fisal Rabin
Keyword(s):  
Hyperspectral Imaging ◽  
Oil Palm ◽  
Fruits And Vegetables ◽  
Imaging System ◽  
Peat Soil ◽  
Mineral Soil ◽  
Plant Management ◽  
Imaging Method ◽  
Fruit Firmness ◽  
Palm Trees

Hyperspectral imaging is a non destructive method that has been used to evaluate internal characteristics of fruits and vegetables. Plant genetics, soil characteristics, and plant management are some of key factors to define the quality of oil palm fresh fruit bunches (FFB) produced. This research was aimed to discriminate the Tenera oil palm FFBs produced by oil palm trees grown from mineral soil and peat soil using a hyperspectral imaging system which utilized a Specim V10 spektrograf. The discrimination was based on their ripeness level, mesocarp firmness, and classification using K-mean clustering. The samples consisted of 61 mineral soil FFBs and 60 peat soil FFBs with three ripeness levels as unripe, ripe, and overripe. Hyperspectral images were recorded and processed using Matlab programs. The spectral reflectance intensities showed the discrimination between both origin soils at wavelength ranges of 700 nm  900 nm. The results also showed higher reflectance intensities of peat soil FFBs than mineral soil FFBs. Correspondingly, Fruit firmness of peat soil FFBs are higher than mineral soil FFBs. Classification using K- mean clustering between reflectance intensities and fruit firmness showed significant clusters for three ripeness levels. These results will be useful for an oil palm FFB sorting machine based on spectral imaging method

Mapping of fatty acids composition in shelled almonds analysed in bulk using a Hyperspectral Imaging system

LWT ◽  
2021 ◽  
Vol 138 ◽  
pp. 110678
Author(s):  
Irina Torres ◽  
Dolores Pérez-Marín ◽  
Miguel Vega-Castellote ◽  
María-Teresa Sánchez
Keyword(s):  
Fatty Acids ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Fatty Acids Composition

scholarly journals Thermal Analysis of Stomatal Response under Salinity and High Light

2021 ◽  
Vol 22 (9) ◽  
pp. 4663
Author(s):  
Aleksandra Orzechowska ◽  
Martin Trtílek ◽  
Krzysztof Michał Tokarz ◽  
Renata Szymańska ◽  
Ewa Niewiadomska ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Initial Response ◽  
Co2 Assimilation ◽  
High Light ◽  
Stomatal Aperture ◽  
Imaging Method ◽  
Stomatal Response ◽  
Time Constants ◽  
Net Co2 Assimilation ◽  
Temporary Response

A non-destructive thermal imaging method was used to study the stomatal response of salt-treated Arabidopsis thaliana plants to excessive light. The plants were exposed to different levels of salt concentrations (0, 75, 150, and 220 mM NaCl). Time-dependent thermograms showed the changes in the temperature distribution over the lamina and provided new insights into the acute light-induced temporary response of Arabidopsis under short-term salinity. The initial response of plants, which was associated with stomatal aperture, revealed an exponential growth in temperature kinetics. Using a single-exponential function, we estimated the time constants of thermal courses of plants exposed to acute high light. The saline-induced impairment in stomatal movement caused the reduced stomatal conductance and transpiration rate. Limited transpiration of NaCl-treated plants resulted in an increased rosette temperature and decreased thermal time constants as compared to the controls. The net CO2 assimilation rate decreased for plants exposed to 220 mM NaCl; in the case of 75 mM NaCl treatment, an increase was observed. A significant decline in the maximal quantum yield of photosystem II under excessive light was noticeable for the control and NaCl-treated plants. This study provides evidence that thermal imaging as a highly sensitive technique may be useful for analyzing the stomatal aperture and movement under dynamic environmental conditions.

scholarly journals Synthetic polarization-sensitive optical coherence tomography by deep learning

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yi Sun ◽  
Jianfeng Wang ◽  
Jindou Shi ◽  
Stephen A. Boppart
Keyword(s):  
Optical Coherence Tomography ◽  
Deep Learning ◽  
Imaging System ◽  
Imaging Modality ◽  
Similarity Index ◽  
Polarization Sensitivity ◽  
Imaging Method ◽  
Optical Coherence ◽  
The Real ◽  
Oct Imaging

AbstractPolarization-sensitive optical coherence tomography (PS-OCT) is a high-resolution label-free optical biomedical imaging modality that is sensitive to the microstructural architecture in tissue that gives rise to form birefringence, such as collagen or muscle fibers. To enable polarization sensitivity in an OCT system, however, requires additional hardware and complexity. We developed a deep-learning method to synthesize PS-OCT images by training a generative adversarial network (GAN) on OCT intensity and PS-OCT images. The synthesis accuracy was first evaluated by the structural similarity index (SSIM) between the synthetic and real PS-OCT images. Furthermore, the effectiveness of the computational PS-OCT images was validated by separately training two image classifiers using the real and synthetic PS-OCT images for cancer/normal classification. The similar classification results of the two trained classifiers demonstrate that the predicted PS-OCT images can be potentially used interchangeably in cancer diagnosis applications. In addition, we applied the trained GAN models on OCT images collected from a separate OCT imaging system, and the synthetic PS-OCT images correlate well with the real PS-OCT image collected from the same sample sites using the PS-OCT imaging system. This computational PS-OCT imaging method has the potential to reduce the cost, complexity, and need for hardware-based PS-OCT imaging systems.

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