Image contrast enhancement for fracture roentgenography

Low contrast profile images are frequently encountered in medical practice and correct interpretation of these images is of vital importance. We propose a development of the traditional singular value decomposition (SVD) by applying a feature selection process on the extracted singular values. The proposal calls for the establishment of a feature space in which the interpretability or perception of information in images for human viewers is enhanced while the noise and blurring are reduced. The region of interest is manually cropped, then histogram equalization (HE) and singular value selection procedure follows for further image presentation. The spectral property of SVD is exploited and singular value selection technique is developed on the analogy to the Fourier domain technique for high frequency enhancement. Our method can generate extra viewpoints of the target images to supplement the HE processing.