IEEE SIGNAL PROCESSING LETTERS, VOL. 6, NO. 10, OCTOBER 1999 249 Enhancement of Document Images Using Multiresolution and Fuzzy Logic Techniques Farook Sattar, Member, IEEE, and David B. H. Tay, Member, IEEE Abstract— This letter presents a method for enhancing doc- ument images based on the multiresolution decomposition and fuzzy logic approach. The document image to be enhanced is obtained from a scanner and is a blurred binary image that is corrupted by additive noise. This type of image occurs in many situations when documents such as checks and credit card receipts become noisy and loww-contrast images after scanning, thereby reducing its quality. Our task is to improve the read- ability of such images by reducing the noise and increasing the sharpness of the text. This is achieved using the multiresolution decomposition, fuzzy logic and contrast enhancement operator. The improvement is shown using simulation examples and com- pared with other enhancement techniques. Index Terms—Document image, enhancement, fuzzy logic, mul- tiresolution. I. INTRODUCTION T HE aim of the paper is to develop an algorithm for the en- hancement of document images which have been blurred and corrupted by additive noise. The algorithm presented here is a further development of the method proposed in [6] by incorporating fuzzy logic. The processing system is shown in Fig. 1. It consists of the multiresolution pyramid (Laplacian) in two dimen- sions that performs the multiresolution decomposition and has been widely used; for example, see [2]. The downsam- pling/upsampling are on the quincunx lattice [1]. is the linear filter used in both the decimation and interpolation process. In the reconstruction stage, two types of nonlinear pro- cessing are performed. The first is the contrast enhancement operator on the coarsest level image. The second is the fuzzy edge detector. Both types of processing will be elaborated later. The output obtained after using the contrast operator, (In Fig. 1), is processed by the fuzzy edge detector. The pur- pose of the fuzzy edge detectors is to extract the edges of the text. Simplicity of computations and ease of implementation motivate us to use the fuzzy edge detectors. Furthermore, other interesting properties such as flexibility and reduction Manuscript received January 15, 1999. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. G. Ramponi. F. Sattar is with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore (e-mail: efsattar@ntu.edu.sg). D. B. H. Tay was with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Republic of Singapore. He is now with the Department of Electronic Engineering, LaTrobe University, Bundoora, Vic. 3083, Australia (e-mail: D.Tay@ee.latrobe.edu.au). Publisher Item Identifier S 1070-9908(99)07978-X. Fig. 1. Block diagram of the system (three-level decomposition and recon- struction stages are shown). of ambiguity in the decision rule are motivating factors for the use of fuzzy logic techniques [4], [5]. The fuzzy edge detector provides an edge-image, which is in general nonbinary (continuous valued in the range [0, 1]). The edge-detector can also made nonfuzzy in the limiting case, i.e., or (binary valued) where the pixel value is one if the corresponding pixel belongs to an edge, and zero otherwise. The edge-image, is multiplied with the highpass image, and this extracts the edge components and suppresses the noise components. The modified highpass image is then added to the lowpass image, which provides which will then be interpolated. The resulting image, is used as the input for the fuzzy edge- detector in order to give the edge-image ( in Fig. 1) at the next finer scale. The above process is repeated up to the finest resolution level II. FUZZY EDGE DETECTOR AND CONTRAST ENHANCEMENT OPERATOR A pixel window of length five is used in the fuzzy edge detector for calculating the pixel variations in five directions 1070–9908/99$10.00  1999 IEEE