Long range correlation is a special kind of information redundancy existing in natural images. The intelligent vision system composed of human eyes and brains can make use of it to implement the functions of image representation, image restoration and image enhancement. This dissertation aims at using it to solve some real problems in image processing. A general method of image processing using long-range correlation is proposed and some implementation algorithms are provided. The work of this dissertation can be summarized as follows:I. Analysis and Progress on Fractal Image Coding1) The fractal image coding technique is discussed from a new point of view. We think its success mainly relies in the use of long range correlation in natural images.2) The Fractal Image Coding in Residue Domain (FBCRD) method is presented. It can improve the coding efficiency while reduce the decoding iteration steps. An optimization method and a fast decoding structure are also introduced, that can further reduce the decoding time.3) The concept and the properties of partial fractal mapping are presented and discussed, which leads to a general theory and framework of a class of hybrid image coding systems. Many concrete image coding/decoding systems can be derived from such a framework. Our example shows the advantageous of the hybrid image coding method.II. Image Information Restoration Based on Long Range Correlation1) For the first time, we propose the idea and the basic algorithm for image restoration using long range correlation, which can be summarized into five basic steps: Extracting, Searching. Matching, Competing and Recovering.2) An error concealment method for information loss in block-based image coding systems is presented. For the cases of contiguous block losses, we provide a progressive error concealment method, so that even when the images are very highly corrupted, we still can get reasonable restoration results.3) Impulse noises are often encountered in image acquisition and communication. We present an impulse noise removal method using long range correlation. The tests on different types of noise and different noise ratios show that our method outperforms many recent published approaches provided by other researchers.4) An impulse noise removal algorithm combing fuzzy technique with long range correlation method is introduced. By using fuzzy rules, some ambiguous pixels in the image can also be processed very well.5) The long range correlation method is used to reduce "Blocking Effect" in images. Experiments show that our method achieves enhanced quality for the IJG version 6.0 of JPEG decoded images both subjectively and objectively.