Evaluation of multichannel Wiener Filters applied to fine resolution passive microwave images of first-year sea ice

Abstract

Over the past two decades passive microwave imaging systems have proven to be effective reconnaissance tools in polar environments. However, the mechanical scan mechanism and high gain electronics characteristic of this class of sensors commonly impart noise and unwanted artifacts to image data they produce, complicating visual analysis and automated classification procedures. The fact that data in individual scan lines are characterized by statistical stationarity and that information in adjacent pixels is highly correlated due to oversampling of these image data suggests that Wiener multichannel filtering techniques may prove effective in this application. Wiener filters applied to passive microwave images of first-year sea ice were constructed. Four major parameters that define the filter (lag or pixel offset between the original and desired scenes, filter length, number of lines in the filter, and weight applied to the empirical correlation functions) were varied. Results were compared visually to assess the effect of each variable on image quality. Effective filters that limit high frequency noise and enhance ice characteristics use a lag of one pixel, consist of two or three channels, are five pixels in length, and weigh the auto- and cross-correlation functions equally.