Texture sensitive denoising for single sensor color imaging devices Angelo Bosco 1 , Sebastiano Battiato 2 , Arcangelo Bruna 1 and Rosetta Rizzo 2 1 STMicroelectronics, Stradale Primosole 50, 95121 Catania - Italy 2 Università di Catania, Dipartimento di Matematica ed Informatica, Viale A. Doria 6, 95125 Catania - Italy angelo.bosco@st.com; battiato@dmi.unict.it; arcangelo.bruna@st.com; rosetta.rizzo@dmi.unict.it; Abstract. This paper presents a spatial noise reduction technique designed to work on CFA (Color Filter Array) data acquired by CCD/CMOS image sensors. The overall processing preserves image details by using heuristics related to HVS (Human Visual System) and texture detection. The estimated amount of texture and HVS sensitivity are combined to regulate the filter strength. Experimental results confirm the effectiveness of the proposed technique. Keywords: Denoising, Color Filter Array, HVS, Texture Detection. 1. Introduction The image formation process through consumer imaging devices is intrinsically noisy. This is especially true using low-cost devices such as mobile-phones, PDA, etc., mainly in low-light conditions and absence of flash-gun. In terms of denoising, linear filters can be used to remove Gaussian noise (AWGN), but they also significantly blur edge structures of an image. Many sophisticated techniques have been proposed to allow edge preserving noise removal such as: [12] and [13] that perform multiresolution analysis and processing in the wavelet domain, [3] that uses anisotropic non-linear diffusion equations but work iteratively, [1] and [10] that are spatial denoising approaches. In this paper we propose a novel spatial noise reduction method that directly processes the raw CFA data, combining together HVS (Human Visual System) heuristics, texture/edges preservation techniques and sensor noise statistics, in order to obtain an effective adaptive denoising. The proposed algorithm introduces the concept of the usage of HVS properties directly on the CFA raw data from the sensor to characterize or isolate unpleasant artifacts.