Infrared Image Enhancement Using Multi-Wavelet Decomposition

Applying multi-wavelet decomposition for hierarchical enhancement can effectively improve the quality of infrared images. This enhancement technique enables clearer observation of details and features within infrared imagery. During the image enhancement process, we utilize information from various wavelet decomposition layers to adjust brightness, contrast, and fine details, achieving superior visual results. The implementation typically involves decomposing the infrared image into multiple frequency sub-bands using wavelet transforms like Daubechies or Symlets, applying enhancement algorithms to each sub-band separately, and then reconstructing the image through inverse wavelet transform. This approach allows for more accurate analysis of infrared images and extraction of valuable information. Therefore, hierarchical enhancement using multi-wavelet decomposition proves to be a highly effective method for infrared image processing, particularly useful in applications requiring precise thermal pattern recognition and detail preservation.