How do you combine radiometric correction with geometric correction and image enhancement?

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Radiometric correction is a process that improves the quality and accuracy of remote sensing images by removing or reducing the effects of atmospheric, sensor, and illumination factors. In this article, you will learn about the different types of radiometric correction, how they are applied, and how they can be combined with geometric correction and image enhancement to produce better results.

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Start with radiometric correction:

Apply radiometric correction first to remove sensor and atmospheric distortions. This ensures the image data is accurate before moving on to geometric corrections and enhancements.### *Follow with geometric correction:Use software like ENVI or ERDAS IMAGINE to correct spatial distortions. This step aligns the image accurately, making subsequent enhancements more effective.

本摘要由 AI 和以下专家提供支持

Moises Salgado

Executive Manager @ Serasa Experian |…
Allan ROSS ???????

高级科学计算工程师（计算机视觉） ???? @TotalEnergies…

1 Types of radiometric correction

There are four main types of radiometric correction: radiometric calibration, atmospheric correction, topographic correction, and sensor normalization. Radiometric calibration converts the digital numbers (DN) of the image pixels to physical units, such as radiance or reflectance. Atmospheric correction removes or reduces the effects of atmospheric scattering, absorption, and haze on the image. Topographic correction adjusts the image for the variations in illumination and reflectance caused by the terrain relief. Sensor normalization harmonizes the images from different sensors or dates by eliminating the differences in radiometric characteristics.

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Allan ROSS ???????

高级科学计算工程师（计算机视觉） ???? @TotalEnergies OneTech CSTJF ??????
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Combining radiometric correction, geometric correction, and image enhancement in remote sensing involves a multi-step process to improve image quality and usability. Radiometric correction is applied first to address sensor calibration, atmospheric effects, and illumination variations. Geometric correction follows to remove spatial distortions, and image enhancement is done last to improve visual interpretability. Integrated workflows in software like ENVI and ERDAS IMAGINE facilitate these steps. Practitioners must choose appropriate methods, assess quality, and balance computational costs to achieve optimal results.

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2 How to apply radiometric correction

The methods and tools for applying radiometric correction vary depending on the type of correction, the sensor, and the image characteristics. For instance, radiometric calibration can be done using calibration coefficients or equations, and many software packages like ENVI or ERDAS IMAGINE have built-in functions for this purpose. Atmospheric correction models and algorithms, such as the Dark Object Subtraction (DOS), Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), or Second Simulation of a Satellite Signal in the Solar Spectrum (6S) are also available. Similarly, software like ENVI or ATCOR offer topographic correction models and algorithms like Cosine Correction, Minnaert Correction, or C Correction. Lastly, sensor normalization techniques like histogram matching, regression-based adjustment, or empirical line method can be employed with software such as ENVI or ERDAS IMAGINE offering built-in functions for this purpose.

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Moises Salgado

Executive Manager @ Serasa Experian | Co-founder & CTO @ Agrosatelite | remote sensing & GIS specialist
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Adjusts for sensor-specific errors and converts raw digital numbers (DN) to reflectance values.Then removes atmospheric effects (e.g., haze, scattering) that can distort the radiance received by the sensor. Radiometric correction is usually performed as the first step, as it ensures that the data used in subsequent processes (like geometric correction and image enhancement) is radiometrically accurate.

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3 How to combine radiometric correction with geometric correction and image enhancement

Radiometric correction is usually performed before geometric correction and image enhancement, as it improves the accuracy and consistency of the image data. Geometric correction is a process that removes or reduces the distortions and errors in the image caused by the sensor, the platform, and the earth's curvature and rotation. Image enhancement is a process that improves the visual quality and interpretability of the image by manipulating its contrast, brightness, color, or spatial resolution. Some software packages, such as ENVI or ERDAS IMAGINE, have integrated workflows for combining radiometric correction with geometric correction and image enhancement.

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4 Benefits of combining radiometric correction with geometric correction and image enhancement

Combining radiometric correction with geometric correction and image enhancement can provide several benefits for remote sensing applications. It can improve the accuracy and reliability of image analysis and classification by reducing noise and variability in the image data. Additionally, it can enhance the comparability and compatibility of images from different sensors or dates by eliminating differences in radiometric and geometric characteristics. Furthermore, it can increase the usability and utility of images for various purposes, such as mapping, monitoring, modeling, or decision making, as it improves the visual quality and clarity of the image.

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5 Challenges of combining radiometric correction with geometric correction and image enhancement

Combining radiometric correction with geometric correction and image enhancement can also present some challenges for remote sensing practitioners. They must choose the appropriate methods and parameters for each type of correction and enhancement, which may depend on the sensor, the image, and the application. Additionally, practitioners must assess the quality and effectiveness of the correction and enhancement processes, as they may introduce errors or artifacts in the image. Furthermore, practitioners must balance the trade-offs between the computational cost and the performance of the correction and enhancement processes as they may require intensive processing and storage resources.

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How do you combine radiometric correction with geometric correction and image enhancement?

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1 Types of radiometric correction

2 How to apply radiometric correction

3 How to combine radiometric correction with geometric correction and image enhancement

4 Benefits of combining radiometric correction with geometric correction and image enhancement

5 Challenges of combining radiometric correction with geometric correction and image enhancement

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