Thursday, November 7, 2013

IMPROVED IMAGE BLUR REMOVAL


The Technology below is available for License. Contact Tamir Huberman at Yissum for more information on the technology

Technology Summary
Fattal Raanan, HUJI, School of Computer Science and Engineering, CS - Computer Vision
tamir_huberman_raanan_fattal2.jpg
Fast method eliminates need for repeated reconstructions of latent image
Categories
Computer Science & Engineering, Imaging/Computer Graphics
Development Stage
Completed
Patent Status
Patent application filed in the United States
Highlights
  • In many practical scenarios, such as hand-held cameras or ones mounted on a moving vehicle, it is difficult to eliminate camera shake. Sensor movement during exposure leads to unwanted blur in the acquired image.
  • Current approaches are based on repeated reconstructions of the latent image, which makes them slow. Furthermore, many methods rely on explicit assumptions that do not always hold and thus undermine the accuracy of the estimated kernel and deblurred image.
  • There is therefore a need for a faster, more accurate method for removing blur in digital images.
Our Innovation
Purely statistical approach to recover blur kernel in motion-blurred natural images by extracting a set of statistics from the input image and using them to recover the blur.
Figure: Kernels estimated by different methods and the resulting deblurred images
Key Features
  • More robust and accurate recovery of blur kernel.
  • Able to cope well with images containing under-resolved texture and foliage clutter in outdoor scenes.
  • Input image only accessed once to extract small set of statistics, so the technique depends mostly on blur kernel size and does not scale with the image dimensions.
  • Method achieves highly accurate results in scenarios that challenge other approaches, at fast running times.
  • Method does not rely on the presence or detection of well-defined step edges at multiple orientations as required by other methods.
Development Milestones
  • Seeking licensing opportunities
The Opportunity
  • By 2016, the digital photography market should reach $82.5 billion.
  • Market researchers have predicted that by 2013, nearly 70% of handsets sold in the United States will come equipped with a camera of 2-megapixels or more and that consumers will respond to this trend by making greater use of mobile imaging software, including photo-editing.

CONTENT-SPECIFIC IMAGE ENHANCEMENT


The Technology below is available for License. Contact Tamir Huberman at Yissum for more information on the technology


Technology Summary
Lischinski Daniel, HUJI, School of Computer Science and Engineering, CS - Computer Vision
tamir_huberman_-_dani_lischinski1.jpg
Automatically enhances parts of image according to context
Categories
Computer Science & Engineering  Imaging / Computer Graphics
Development Stage
Research complete
Patent Status
Patent application filed in the United States
Highlights
  • Digital images captured by non-professional photographers requires effective automatic photo enhancement.
  • Most current systems manipulate tone and color over the whole image without understanding and accounting for the content of the image.
Our Innovation
Photo enhancement method that automatically improves the quality of specific image elements such as the sky, human faces, and underexposed salient regions by intelligently taking into account local and global semantics.
Figure 1: Comparison of original on left and results of new method on right
Figure 2: Input images (first left) are compared with our results (second), Photoshop Elements (third), Microsoft Office Picture Manager (fourth) and Google’s Picasa (fifth) 
Key Features
  • Intelligently combines a variety of local tone mapping and color correction operations while taking into account image content.
  • Using existing robust detectors of sky and people, image areas containing human faces, skin, blue sky and clouds, as well as salient underexposed parts of the scene are subjected to customized enhancement operators.
  • Consistently significantly improves the majority of images
  • Outperforms the automatic enhancement operators available in several popular products
Development Milestones
  • Seeking cooperation for licensing and commercialization
The Opportunity
  • Currently, 30 billion images a year are uploaded to Facebook
  • Automatic photograph enhancement tools are included in such popular commercial software packages as Adobe Photoshop, Microsoft Office Picture Manager, Google Picasa, and others.