Ten lectures on wavelets
Accurate Recovery of Three-Dimensional Shape from Image Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Degraded Image Analysis: An Invariant Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting the Optimal Focus Measure for Autofocusing and Depth-From-Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identification of tuberculosis bacteria based on shape and color
Real-Time Imaging - Special issue on imaging in bioinformatics: Part III
Measure of image sharpness using eigenvalues
Information Sciences: an International Journal
New focus assessment method for iris recognition systems
Pattern Recognition Letters
A passive auto-focus camera control system
Applied Soft Computing
Shape from focus using fast discrete curvelet transform
Pattern Recognition
A Derivative-Based Fast Autofocus Method in Electron Microscopy
Journal of Mathematical Imaging and Vision
Efficient blur estimation using multi-scale quadrature filters
Signal Processing
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We present a new measure of image focus. It is based on wavelet transform of the image and is defined as a ratio of high-pass band and low-pass band norms. We show this measure is monotonic with respect to the degree of defocusation and sufficiently robust. We experimentally illustrate its performance on simulated as well as real data and compare it with existing focus measures (gray-level variance and energy of Laplacian). Finally, an application of the new measure in astronomical imaging is shown.