FOCUS ERROR ESTIMATION IN IMAGES

Patent №

US 8,917,346

Granted

2014-12-23

Filed 2013

Owner

Lab

AI components

3

ml · vision · hardware

Assignment

None on record

Dataset

AIPD

2023_r1 edition

Application

13965758

Estimating focus error in an image involves a training phase and an application phase. In the training phase, an optical system is represented by a point-spread function. An image sensor array is represented by one or more wavelength sensitivity functions, one or more noise functions, and one or more spatial sampling functions. The point-spread function is applied to image patches for each of multiple defocus levels within a specified range to produce training data. Each of the images for each defocus level (i.e. focus error) is sampled using the wavelength sensitivity and spatial sampling functions. Noise is added using the noise functions. The responses from the sensor array to the training data are used to generate defocus filters for estimating focus error within the specified range. The defocus filters are then applied to the image patches of the training data and joint probability distributions of filter responses to each defocus level are characterized. In the application phase, the filter responses to arbitrary image patches are obtained and combined to derive continuous, signed estimates of the focus error of each arbitrary image patch.

Machine learningVisionAI hardwareH04N 23/70G02B 7/36H04N 23/672H04N 23/673

AI classification

Vision1.00
Machine learning0.91
AI hardware0.66
Knowledge representation0.22
Evolutionary computation0.01
Planning0.00
Natural language0.00
Speech0.00
© 2026 NYSGPT2525 LLC