Raw image format

A camera raw image file contains unprocessed or minimally processed data from the of either a digital camera, a motion picture film scanner, or other . Raw files are so named because they are not yet processed, and contain large amounts of potentially redundant data. Normally, the image is processed by a raw converter, in a wide-gamut internal color space where precise adjustments can be made before to a viewable file format such as JPEG or PNG for storage, printing, or further manipulation. There are dozens of raw formats in use by different manufacturers of digital image capture equipment. Rationale Raw image files are sometimes incorrectly described as "digital negatives". Rather, the raw datasets are more like exposed but film which can be converted (electronically developed) in a non-destructive manner multiple times in observable, reversible steps to reach a visually desired image. (With exposed film, development is a single event that physically transforms the u

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On Local Features for Face Verification

{W}e compare four local feature extraction techniques for the task of face verification, namely (ordered in terms of complexity): raw pixels, raw pixels with mean removal, 2D Discrete Cosine Transform (DCT) and local Principal Component Analysis (PCA). The comparison is performed in terms of discrimination ability and robustness to illumination changes. We also evaluate the effectiveness of several approaches to modifying standard feature extraction methods in order to increase performance and robustness to illumination changes. Results on the XM2VTS database suggest that when using a Gaussian Mixture Model (GMM) based classifier, the raw pixel technique provides poor discrimination and is easily affected by illumination changes; the mean removed raw pixel technique provides performance that is fairly close to 2D DCT and local PCA, but is considerably affected by illumination changes. The performance of 2D DCT and local PCA techniques is quite similar, suggesting that the 2D DCT technique is to be preferred over the local PCA technique, due to the lower complexity of the 2D DCT. Both 2D DCT and local PCA techniques are considerably more robust to illumination changes compared to the raw pixel techniques. Modifying the 2D DCT and local PCA techniques by removing the first coefficient, which is deemed to be the most affected by illumination changes, clearly enhances robustness; removing more than the first coefficient causes a noticeable reduction in performance on clean images and provides no further gains in robustness. Compared to just throwing out the first coefficient, the use of deltas can achieve a small increase in performance and robustness. Lastly, we suggest that it is more appropriate to use analysis blocks of size 8x8 (as opposed to 16x16) with 2D DCT decomposition; out of the 64 resulting coefficients, the second through to 21-st (resulting in 20 dimensional feature vectors) are the most robust to illumination changes while providing good discriminatory information.

IDIAP2004

DiffuserCam Project

William Cappelletti, Matteo Pariset, Jonathan Philippe Reymond

We test the reconstruction power of a lensless cam- era on a custom dataset. We define a linear inverse problem on the raw image, based on a PSF estimation of the the sensing device and the actual captures. We implement various regularizations to enforce some priors on the reconstructed images and optimize their parameters against some data fidelity scores. Finally we discuss the results, highlighting strengths and drawback of signal processing techniques.

2021

Joint Demosaicing and Super-Resolution Imaging from a Set of Unregistered Aliased Images

Karim Krichane, Sabine Süsstrunk, Patrick Vandewalle

We present a new algorithm that performs demosaicing and super-resolution jointly from a set of raw images sampled with a color filter array. Such a combined approach allows us to compute the alignment parameters between the images on the raw camera data before interpolation artifacts are introduced. After image registration, a high resolution color image is reconstructed at once using the full set of images. For this, we use normalized convolution, an image interpolation method from a nonuniform set of samples. Our algorithm is tested and compared to other approaches in simulations and practical experiments.

2007

Digital photography

Digital photography uses cameras containing arrays of electronic photodetectors interfaced to an analog-to-digital converter (ADC) to produce s focused by a lens, as opposed to an exposure on phot

Digital camera

A digital camera is a camera that captures photographs in digital memory. Most cameras produced today are digital, largely replacing those that capture images on photographic film. Digital cameras a

Multi-exposure HDR capture

In photography and videography, multi-exposure HDR capture is a technique that creates extended or high dynamic range (HDR) images by taking and combining multiple exposures of the same subject matt

MICRO-511: Image processing I

Introduction to the basic techniques of image processing. Introduction to the development of image-processing software and to prototyping in JAVA. Application to real-world examples in industrial vision and biomedical imaging.

MICRO-512: Image processing II

Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in JAVA; application to real-world examples in industrial vision and biomedical imaging.

MSE-451: Polymer morphological characterization techniques

Sample preparation and direct observation techniques (optical microscopy, AFM, electron microscopy) and their practical application to the study of morphology and microdeformation in polymers.