Robust Pre-processing and Post-processing Methods for 2D Gel Electrophoresis Images using Non- Separable Quincunx Wavelet

One of the most important tasks performed in proteomics is correct analysis and interpretation of 2D electrophoresis gel images. The nonlinearities in the gel formation and image acquisition process leads to distortions, overlapped protein spots, saturated spots, faint spots, nonlinear intensity and uneven background in the gel images. As a result, pre-processing and post processing steps are very challenging tasks for precise protein identification. The preprocessing step includes the task of removing additive or multiplicative noises and edge enhancement. The solutions available in the literature have failed to give satisfactory results. Non-separable wavelet processing methods, due to their inherent ability to be able to better represent directional information, seem to be promising for the processing of 2D gel images. In this paper, we explore approaches based on quincunx non-separable filterbanks for image pre-processing and post-processing. A novel method for edge preserved de-noising of gel images has been presented which also removes multiplicative noises. Our experiments show that nonseparable wavelets are well suited for removing multiplicative noise. Our multi-scale post-processing method effectively removes the present streaks in the gel images.