Low Memory Cost Bilateral Filtering Using Stripe-based Sliding Integral Histogram

Abstract

Bilateral filter can well smooth images while preserving edges, and thus has been widely used in various applications. However, it needs significant memory cost due to a whole image storage. This paper develops three methods to significantly reduce the memory cost. The runtime updating method (RUM) discards unnecessary data in runtime. The stripe-based integral histogram method (SBM) divides image into vertical image-stripes. The sliding origin method (SOM) sliding moves the origin of integration region to achieve the most memory reduction. The final result shows that the proposed approach only needs 24Kbits memory, which saves 99.993% of memory cost for smoothing a VGA-sized image with 30-fps speed, when compared to the previous optimized constant time integral histogram approach.