A CT Image Denoising Method Based on Projection Domain Feature
This addresses noise reduction in CT imaging for industrial applications, but it appears incremental as it builds on existing projection domain methods.
The paper tackled the problem of noise in reconstructed CT images from increased projection sampling by proposing a projection domain denoising algorithm that uses similarity between neighboring views to reduce noise, with validation through numerical simulation and practical experiments.
In order to improve image quality of projection in industrial applications, generally, a standard method is to increase the current or exposure time, which might cause overexposure of detector units in areas of thin objects or backgrounds. Increasing the projection sampling is a better method to address the issue, but it also leads to significant noise in the reconstructed image. This paper proposed a projection domain denoising algorithm based on the features of the projection domain for this case. This algorithm utilized the similarity of projections of neighboring veiws to reduce image noise quickly and effectively. The availability of the algorithm proposed in this work has been conducted by numerical simulation and practical data experiments.