Medical image enhancement in F-shift transformation domain

Area of Science:

• Medical Imaging
• Image Processing
• Biomedical Engineering

Background:

• Medical image enhancement is crucial for accurate diagnosis and treatment.
• Existing methods may lack efficiency or comprehensive features.
• The need for integrated enhancement and compression techniques is growing.

Purpose of the Study:

• To propose an automated medical image enhancement method.
• To integrate image enhancement with data compression.
• To support clinical diagnosis, adjuvant therapy, and curative effect evaluation.

Main Methods:

• Utilizing contrast limited adaptive histogram equalization (CLAHE) in the F-shift transformation domain.
• Adjusting image brightness for underexposed or overexposed images.
• Applying CLAHE to low-frequency components after two-dimensional F-shift transformation (TDFS) and zeroing high-frequency coefficients.
• Reconstructing the image using inverse transformation and further enhancing with CLAHE.

Main Results:

• The proposed method demonstrates superior image enhancement performance compared to existing techniques.
• Experimental results validate the effectiveness of the CLAHE and F-shift transformation approach.
• The method achieves a notable degree of data compression alongside enhancement.

Conclusions:

• The integrated approach offers significant improvements in medical image quality.
• The technique provides a valuable tool for clinical applications requiring high-fidelity images.
• The dual capability of enhancement and compression makes this method highly efficient.