What are the differences between hyperspectral cameras and ordinary cameras?

I. Differences in Working Principles

The working principle of a camera

The principle is simple and straightforward. It captures light through the lens, and after the light is focused by the lens, it is projected onto the image sensor. The pixels in the image sensor generate corresponding electrical signals based on the received light intensity. These electrical signals, after a series of processing and conversion, eventually form the image we see. Ordinary cameras usually only perceive and record light within the visible light range. Their focus mainly lies in the basic features of objects such as shape, color and texture, in order to present a clear picture that conforms to the visual habits of the human eye.

The working principle of hyperspectral cameras

The principle is much more complex. It can not only capture the information of an object in the visible light region, but also simultaneously obtain spectral information in multiple bands such as near-infrared and mid-infrared. When a hyperspectral camera is in operation, it decomposes light into spectral components of different wavelengths and then images the light reflected or emitted by objects at each wavelength separately. This imaging method is similar to conducting a "spectral scan" on an object, which can obtain rich information about the object in different spectral bands. By analyzing these spectral information, we can gain a deep understanding of the physical and chemical properties of objects, and even identify their composition and structure.

Ii. Differences in Data Acquisition Capabilities
In terms of data acquisition, there is a world of difference between ordinary cameras and hyperspectral cameras. Photos taken by ordinary cameras are usually two-dimensional images, with each pixel containing only limited information such as color and brightness. A common color photo usually has each pixel composed of three color channels: red, green and blue. Various colors are presented through the combination of these three channels. Although ordinary cameras can obtain photos with different effects by adjusting shooting parameters such as ISO, shutter speed, aperture, etc., generally speaking, the data dimensions they obtain are relatively low, mainly focusing on the visual presentation of the image.

Hyperspectral cameras can obtain high-dimensional data cubes. In addition to two-dimensional spatial information, it also contains one-dimensional spectral information. Each pixel in this data cube corresponds to a complete spectral curve, recording the reflection or emission characteristics of the object at different wavelengths. This high-dimensional data provides extremely rich information resources for subsequent analysis and processing. For instance, in the agricultural sector, by analyzing the spectral features in hyperspectral images, one can accurately determine the growth status of crops, the situation of pests and diseases, as well as soil fertility and other information. In environmental monitoring, hyperspectral cameras can detect the components and concentrations of pollutants in water bodies, as well as changes in gas components in the atmosphere, etc.

Iii. Differences in application fields
Due to the differences in working principles and data acquisition capabilities, hyperspectral cameras and ordinary cameras also have their own focuses in application fields.

Ordinary cameras are widely used in various aspects of daily life, such as photography enthusiasts capturing beautiful moments, news media taking news pictures, and commercial photography for product promotion, etc. It plays a significant role in scenarios such as social media, tourism, and family memorials, mainly meeting people's demands for visual aesthetics and documenting their lives. In addition, ordinary cameras also have certain applications in some basic scientific research fields, such as the observation of macroscopic biological forms in biology and the recording of simple experimental phenomena in physics.

Hyperspectral cameras are mainly applied in professional scientific research, industrial and military fields. In terms of scientific research, it provides powerful tools for the study of disciplines such as astronomy, geology and ecology. For instance, astronomers can use hyperspectral cameras to analyze the spectral characteristics of celestial bodies, thereby understanding their chemical composition and physical state. Geologists can identify different rock types and mineral resources through hyperspectral images. In the industrial field, hyperspectral cameras can be used for product quality inspection, food component analysis, material identification, etc. For instance, in the food processing industry, it can detect impurities, moisture content and nutritional components in food, ensuring the quality and safety of food. In the military field, hyperspectral cameras can be used for tasks such as target reconnaissance, camouflage recognition, and environmental monitoring. They can identify hidden targets through camouflage materials, providing important intelligence support for military decision-making.

Iv. Characteristics of Imaging Effects
In terms of imaging effect, ordinary cameras pursue visual effects with bright colors, high contrast and good clarity to meet people's appreciation needs for beautiful pictures. Ordinary cameras strive to present realistic and vivid scenes in photos by optimizing the optical performance of lenses, image sensor technology and image processing algorithms, making the colors and details of objects more realistic.

The imaging effect of hyperspectral cameras focuses more on the accuracy and completeness of spectral information. The images it captures may not be visually as bright and eye-catching as ordinary photos, but they contain rich inner information. Each pixel in a hyperspectral image represents the spectral response of an object at a specific wavelength. By analyzing these spectral data, various characteristics of the object can be obtained. For instance, in hyperspectral images, different substances may exhibit distinct spectral characteristic curves. Even if they look very similar in appearance, they can still be accurately distinguished through spectral analysis. This imaging effect is of crucial significance for application scenarios that require precise identification and analysis of object components.

V. Equipment Cost and Complexity
The technical complexity of hyperspectral cameras determines that they are far more expensive in terms of equipment cost and operational difficulty than ordinary cameras. The research and development of hyperspectral cameras involves advanced technologies from multiple fields such as optics, spectroscopy, electronics, and signal processing. Its manufacturing process requires the use of high-precision optical components and advanced detectors, and the cost of these parts is relatively high. In addition, to ensure that hyperspectral cameras can accurately obtain and process spectral information, they also need to be equipped with professional software and algorithms, which further increases their research and development and production costs.

In contrast, the technology of ordinary cameras has become relatively mature, and the market competition is fierce. Their manufacturing costs are relatively low, and the prices are also more affordable. The operation of a regular camera is relatively simple. Users only need to master some basic shooting skills to easily get started with it. The operation of hyperspectral cameras requires professional knowledge and skills. Operators need to understand the basic principles of spectroscopy and related data processing methods in order to fully leverage their advantages and obtain accurate and valuable information.