Video enhancement using per-pixel virtual exposures

By Eric P. Bennett, Leonard McMillan. ACM Transactions on Graphics, 2005

304 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/201fed356fc9d39d3b9d81b029ba71cc798cc7ec

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

Citations in the corpus

A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach (2006, unknown): “2006; Sand and Teller 2006), and video processing (Bennett and McMillan 2005; Winnemöller et al. 2006).”
A fusion-based enhancing method for weakly illuminated images (2016, unknown): “Three major approaches include histogram-based methods [1,5–14], Retinex-based methods [15] [16] [17] [18] [19] [20] [21] and filteringbased methods [22] [23] [24] [25] [26] [27] [28].”
Real-time O(1) bilateral filtering (2009, background): “Originally introduced by Tomasi and Manduchi [2], bilateral filters are edge preserving operators that have found widespread use in many computer vision and graphics tasks like denoising [3, 4, 5, 6, 7], texture editing and relighting [8], tone management [9, 10], demosaicking [11], stylization [12]”
Image deblurring with blurred/noisy image pairs (2007, methodology): “Denoising can be performed by a joint/cross bilateral filter using flash/no-flash images [Petschnigg et al. 2004; Eisemann and Durand 2004], or by a spatio-temporal filter for video sequences [Bennett and McMillan 2005].”
Multiresolution Bilateral Filtering for Image Denoising (2008, unknown): “In addition to image denoising, the bilateral filter has also been used in some other applications, including tone mapping [27], image enhancement [28], volumetric denoising [29], exposure correction [30], shape and detail enhancement from multiple images [31], and retinex [32].”
Burst photography for high dynamic range and low-light imaging on mobile cameras (2016, methodology): “Our approach takes inspiration from frequency-domain video denoising techniques that operate on 3D stacks of matching images patches [Kokaram 1993; Bennett and McMillan 2005; Dabov et al. 2007a].”