Heide et al., 2016 - Google Patents
Proximal: Efficient image optimization using proximal algorithmsHeide et al., 2016
View PDF- Document ID
- 1637884059079166781
- Author
- Heide F
- Diamond S
- Nießner M
- Ragan-Kelley J
- Heidrich W
- Wetzstein G
- Publication year
- Publication venue
- ACM Transactions on Graphics (TOG)
External Links
Snippet
Computational photography systems are becoming increasingly diverse, while computational resources---for example on mobile platforms---are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image …
- 238000005457 optimization 0 title abstract description 87
Classifications
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- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06T5/001—Image restoration
- G06T5/002—Denoising; Smoothing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06T5/001—Image restoration
- G06T5/003—Deblurring; Sharpening
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- G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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