Multiscale Contrast Enhancement and Denoising in Digital Radiographs
This chapter presents a detailed mathematical analysis of a dyadic wavelet transform and reveals its connection to traditional techniques of unsharp masking. It proposes a simple nonlinear enhancement function and analyzes the problem of introducing artifacts, as a result of wavelet processing. The chapter describes an explicit denoising stage that preserves edges using wavelet shrinkage and adaptive thresholding. It also presents a one-dimensional dyadic wavelet transform and analyzes linear enhancement and its mathematical connection to traditional unsharp masking. The chapter also analyzes simple nonlinear enhancement by point-wise functional mapping. It introduces denoising with wavelet shrinkage along with an adaptive approach for finding threshold values. The chapter discusses a two-dimensional extension for digital mammography and special procedures developed for denoising and enhancement that avoid orientation distortions. It provides some sample experimental results and comparisons with existing techniques. Denoising a radiograph is a very difficult problem for several reasons.