US 12,244,979 B2
Defective pixel detection
Jing-Fei Ren, Plano, TX (US); Hrushikesh Garud, Bangalore (IN); Rajasekhar Allu, Plano, TX (US); Gang Hua, Katy, TX (US); Niraj Nandan, Plano, TX (US); Mayank Mangla, Allen, TX (US); and Mihir Narendra Mody, Bangalore (IN)
Assigned to TEXAS INSTRUMENTS INCORPORATED, Dallas, TX (US)
Filed by TEXAS INSTRUMENTS INCORPORATED, Dallas, TX (US)
Filed on Nov. 9, 2022, as Appl. No. 17/983,905.
Claims priority of provisional application 63/392,951, filed on Jul. 28, 2022.
Prior Publication US 2024/0040096 A1, Feb. 1, 2024
Int. Cl. H04N 9/64 (2023.01); G06T 7/00 (2017.01); G06T 7/90 (2017.01)
CPC H04N 9/646 (2013.01) [G06T 7/0002 (2013.01); G06T 7/90 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/30168 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method, comprising:
identifying a color channel of an image pixel in a frame;
identifying a threshold function based on the color channel;
identifying one or more nearest-neighboring image pixels with respect to the image pixels, in which the nearest-neighboring image pixels are of the color channel of the image pixel;
applying the threshold function to the one or more nearest-neighbor image pixel values to obtain a threshold value; and
determining whether a corresponding sensor pixel is defective based on a comparison of the image pixel to the threshold value
wherein the identifying of the threshold function further includes identifying an offset pattern of the one or more nearest-neighboring image pixels specific to a subset of color channels to which the image pixel and the one or more nearest-neighboring pixels belong.