Real Time Edge Detection of Objects in Pictures and Videos, without Artifacts

Fattal Raanan, HUJI, School of Computer Science and Engineering, Computer Science


A New family of second-generation wavelets constructed using robust data-prediction lifting scheme



  • Almost every application for manipulating and improving photographic images, such as noise reduction and detail enhancement, relies on scale separation.
  • Linear translation-invariant (LTI) filtering is the classic and efficient method for achieving scale separation; however the method generates visual artefacts such as halos.
  • Edge-preserving smoothing filters avoid these artefacts but are computationally expensive, they are time-consuming and often increase memory requirements.
  • The new wavelets accelerate the computation of the edge-preserving smoothing as well as various other popular applications (such as image colorization) at  no memory cost.

Our Innovation

Family of second-generation wavelets constructed using robust data-prediction lifting schemes. The wavelets make it possible to compute nonlinear data-dependent multi-scale edge-preserving image filtering and processing at computation times which are linear in the number of image pixels.

Key Features

  • Avoids halo artefacts in band-independent multi-scale processing with minimal computational cost and without taking any special precautions.
  • Can be used to compute edge-aware interpolation schemes very efficiently, enabling real-time implementation of various applications such as image colorization
  • Avoids the difficulties of solving large and poorly conditioned systems of equations
  • Significantly accelerates various computational photography applications, achieving multi-scale data-dependent filtering at running times typical of linear translation-invariant (LTI) filtering.

The Opportunity

  • The software is ready for incorporation into any image processing toolkit or video processing system to provide significantly faster results at reduced cost. It has particular benefits for:
  • Edge-preserving smoothing of color images
  • Edge-aware noise removal
  • Dynamic-range compression
  • Scattered data interpolation for image colorization

Patent Status

Granted US 8,295,632

Contact for more information:

Anna Pellivert
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