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Nighttime Image Stitching Method Based on Guided Filtering Enhancement.

Mengying Yan1, Danyang Qin1, Gengxin Zhang1

  • 1Department of Electronic Engineering, Heilongjiang University, Harbin 150080, China.

Entropy (Basel, Switzerland)
|September 23, 2022
PubMed
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This summary is machine-generated.

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This study introduces an adaptive image enhancement algorithm using guided filtering to improve nighttime image stitching. The method enhances details and color, increasing feature matching for accurate panoramic image generation in low-light conditions.

Area of Science:

  • Computer Vision
  • Image Processing

Background:

  • Image stitching is crucial for applications like geological surveys and military reconnaissance.
  • Existing methods struggle with low-light conditions and feature loss, especially in nighttime images with extreme brightness variations.
  • This limits the accuracy and applicability of current image stitching technologies.

Purpose of the Study:

  • To address the limitations of current image stitching techniques in low-light and nighttime environments.
  • To propose an adaptive image enhancement algorithm for preprocessing nighttime images prior to feature registration.
  • To improve the accuracy and quality of panoramic images generated from challenging lighting conditions.

Main Methods:

  • An adaptive image enhancement algorithm based on guided filtering was developed.
Keywords:
feature matchingguided filteringimage stitchingnighttime image enhancement

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  • The proposed algorithm preprocesses nighttime images to improve detail and color restoration.
  • Feature registration is then performed on the enhanced images to increase feature matching points.

    • Main Results:

    • The enhancement algorithm significantly improves detail performance and color restoration in nighttime images.
    • Preprocessing nighttime images enhances overall image quality for subsequent processing.
    • The number of feature matching points increased, leading to higher accuracy in image stitching.

    Conclusions:

    • The proposed adaptive image enhancement algorithm effectively overcomes the challenges of stitching nighttime images.
    • Enhanced image quality and increased feature matching lead to improved panoramic image generation.
    • This approach meets the practical application requirements for image stitching in diverse lighting conditions.