Blind detection and compensation for BIB detector infrared images
CSTR:
Author:
Affiliation:

1Mathematics and Science College, Shanghai Normal University, Shanghai 200233, China;2Terahertz Technology Innovation Center, The fiftieth Research Institute of China Electronic Technology Group Corporation, Shanghai 200331, China

Clc Number:

TN219

Fund Project:

Supported by the National Natural Science Foundation of China (62171286,62301321); the Shanghai Sailing Program (23YF1444300,22YF1446200,22YF1446300); Program of Shanghai Academic/Technology Research Leader(21XD1423600).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Due to the influence of materials and processes, infrared images generally suffer from the problem of blind pixels. For infrared images from new Blocked Impurity Band (BIB) detectors, there are still issues such as limited dynamic range and significant non-uniformity. Conventional blind pixel detection and compensation methods are not fully applicable to BIB detector images. To address this issue, this paper enumerates the pros and cons of common methods for detecting and compensating blind pixels in infrared images and conducts experimental processing on actual measured BIB images one by one. However, the results indicate that the distribution of blind pixels is highly non-uniform, with a relatively high proportion of clustered blind pixels. Therefore, this paper proposes an improved blind pixel detection method and a blind pixel compensation method, and implements the algorithms using an FPGA-based hardware system platform. The analysis shows that the uniformity of blind pixel distribution and the proportion of clustered blind pixels have been optimized after the improvement, leading to a tangible enhancement in their economic viability for application.

    Reference
    Related
    Cited by
Get Citation
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 10,2025
  • Revised:March 07,2026
  • Adopted:January 08,2026
  • Online: March 01,2026
  • Published:
Article QR Code