T HE very high spectral resolution of remotely sensed hyperspectral data [1], rooted in technological, modeling and processing advances, has fostered a strong interest in this image modality at an unprecedented rate in recent years. In fact, the very high spectral resolution of hyperspectral data offers very significant potential in the identification of materials and their properties [2]. Howe...

This research paper explores focused on developing an automatic mango fruit quality detection system using a combination of artificial intelligence and the Internet Things technologies. The utilizes hyperspectral camera to capture images image processing techniques analyze images. Deep learning algorithms are employed classify based parameters such as ripeness, size, color. proposed aims automa...

Real-time image processing requires high computational and I/O throughputs obtained by use of optoelectronic system solutions. A novel architecture that uses focal-plane optoelectronic-area I/O with a fine-grain, low-memory, single-instruction-multiple-data (SIMD) processor array is presented as an efficient computational solution for real-time hyperspectral image processing. The architecture i...

Hyperspectral image compression is an important task in remotely sensed Earth Observation as the dimensionality of this kind of image data is ever increasing. This requires on-board compression in order to optimize the donwlink connection when sending the data to Earth. A successful algorithm to perform lossy compression of remotely sensed hyperspectral data is the iterative error analysis (IEA...

One of the objectives of precision agriculture is rapid location of fields information to reduce the investment and improve the environment. Based on near infrared (NIR) hyperspectral images, this paper outlines an approach using hyperspectral imaging technology, combining spectral analysis methods and supervised classification methods for the extraction and analysis of farmland objects. This p...

We describe a novel approach to produce color composite images from hyperspectral data using weighted spectra averages. The weighted average is based on a sequence of numbers (weights) selected using pixel value information and interband distance. Separate sequences of weights are generated for each of the three color bands forming the color composite image. Tuning of the weighting parameters a...

Hyperspectral image is a sequence of images generated by hundreds of detectors. Each detector is sensitive only to a narrow range of wavelengths. One can view such an image sequence as a three-dimensional array of intensity values (pixels) within a rectangular prism. This image prism reveals contiguous spectrum information about the composition of the area being viewed by the instrument. The pr...

A hyperspectral imaging system demonstrated potential to detect surface fecal and ingesta contaminants on poultry carcasses. Hyperspectral imagery were processed and analyzed with four pre-processing methods considering calibration and spectral smoothing approaches. A band-ratio image processing algorithm, using 2-wavelengths (I565/I517) and 3-wavelengths (I576 I616)/ (I529 I616) equations, was...

Hyperspectral imaging is increasingly used in various environmental measurement applications. Airborne hyperspectral sensors enables ground sampling distances (GSD) below 1 meter with high spectral resolution. In order to utilize this data in quantitative remote sensing applications, an accurate radiometric correction of the imagery has to be performed. In this article we present a radiometric ...