A New Focus Measure Using Block Maxima of Image Gradients

Abstract

Auto-focusing is an important problem for various imaging systems. A good focus measure, or evaluation function, is critical for the accomplishment of this task. Some evaluation functions are introduced. Analysis is done on evaluation functions using global data such as the squared image gradient magnitude of the whole image, asserting that these approaches may suffer from the indiscriminate use of the data. A new evaluation function is proposed. By partitioning the image into small blocks and using the maximal squared gradient magnitude in each block to construct the evaluation value, impacts of strong off-boundary gradients deteriorating the performance of the "global" approaches can be suppressed. Experiments on a real-world microscopy video data set show that our method exhibits higher focusing accuracy.

3D Digital Microscopy for Characterizing Punchworks on Medieval Panel Paintings

“…In the literature, several approaches have been introduced, and most of them are based on kernel convolution [Pertuz et al 2013;Zhao et al 2013;Muhammad et al 2012;Pertuz et al 2010;Mahmood 2010;Wu et al 2009;Riaz et al 2008;Malik at al. 2008;Sun at al.…”