While many existing CT noise filtering post-processing techniques optimize minimum mean squared error (MSE)-based quality metrics, it is well-known that the MSE is generally not related to the diagnostic quality of CT images. In medical image quality …
We propose a wavelet based metric of blurriness in the digital images named CogACR – Center of gravity of the Average Cone Ratio. The metric is highly robust to noise and able to distinguish between a great range of blurriness. To automate the CogACR …
With extensive technological advancements in electronic imaging today, high image quality is becoming an imperative necessity in the modern imaging systems. An important part of quality assurance are techniques for measuring the level of image …
We propose a real-time system for blur estimation using wavelet decomposition. The system is based on an emerging multi-core microprocessor architecture (Cell Broadband Engine, Cell BE) known to outperform any available general purpose or DSP …
In this paper, we propose a new algorithm for objective blur estimation using wavelet decomposition. The central idea of our method is to estimate blur as a function of the center of gravity of the average cone ratio (ACR) histogram. The key …