Image enhancement and space-variant color reproduction method for endoscopic images using adaptive sigmoid function

Area of Science:

• Medical Imaging
• Computer Vision
• Image Processing

Background:

• Endoscopic imaging is crucial for diagnosing internal conditions.
• Standard endoscopic images often lack sufficient detail and color accuracy.
• Enhancement techniques are needed to improve diagnostic capabilities.

Purpose of the Study:

• To develop an adaptive image enhancement and space-variant color reproduction method for endoscopic images.
• To improve the visibility of critical tissue and vascular characteristics.
• To enhance the accuracy of pit pattern visualization in lesions and polyps.

Main Methods:

• Color images are converted to YCBCR color space, separating luminance and chrominance.
• An adaptive sigmoid function is applied to luminance pixels for enhancement.
• Space-variant color reproduction modifies chrominance based on texture information.
• Final RGB images are reconstructed from enhanced luminance and chrominance components.

Main Results:

• The proposed method effectively highlights tissue, vascular characteristics, and pit patterns.
• Visual quality and color reproduction efficiency are improved compared to existing methods.
• The technique demonstrates superior focus value and statistical visual representation.

Conclusions:

• The adaptive sigmoid function method offers significant improvements in endoscopic image quality.
• This technique enhances diagnostic accuracy by providing clearer visualization of subtle details.
• The approach is efficient and effective for real-time endoscopic applications.