Ms. Manisha Raut Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 5, Issue 3, ( Part -4) March 2015, pp.73-77 www.ijera.com 73 | Page Review on Various Algorithm for Cloud Detection and Removal for Images Ms.Manisha Raut, Ms.Pallavi Dhok Dept. Of Electronics and Telecommunication Rajiv Gandhi College of Engineering & Research Nagpur, India Dept. Of Electronics and Telecommunication Rajiv Gandhi College of Engineering & Research Nagpur, India Abstract Clouds is one of the significant obstacles in extracting information from tea lands using remote sensing imagery Different approaches have been attempted to solve this problem with varying levels of success In the past decade, a number of cloud removal approaches have been proposed . In this paper we review and discuss about the cloud detection & removal, need of cloud computing , its principles, and cloud removal process and various algorithm of cloud removal. This paper attempts to give a recipe for selecting one of the popular cloud removal algorithms like The Information Cloning Algorithm, Cloud Distortion Model And Filtering Procedure, Semi- Automated Cloud/Shadow, And Haze Identification And Removal etc. A cloud removal approach based on information cloning is introduced...Using generic interpolation machinery based on solving Poisson equations, a variety of novel tools are introduced for seamless editing of image regions. The patch-based information reconstruction is mathematically formulated as a Poisson equation and solved using a global optimization process. Based on the specific requirements of the project that necessitates the utilization of certain types of cloud detection algorithms is decided Keywords- Cloud removal, information cloning, Poisson Equation, Haze Identification And Removal, cloud computing etc. I. INTRODUCTION Globally, the Enhanced Thematic Mapper Plus (ETM+) land scenes are, on average, about 35% cloud covered, as reported by Ju and Roy [1], indicating that cloud covers are generally present in optical satellite images. This phenomenon limits the usage of optical images and increases the difficulty of image analysis. Thus, considerable research efforts have been devoted to the topic of cloud removal to ease the difficulties caused by cloud covers [2]–[7]. If multitemporal images are acquired, the cloud-cover problem has a chance to be eased by reconstructing the information of cloud contaminated pixels under the assumption that the land covers change insignificantly over a short period of time. In the past decade, a number of cloud removal approaches have been proposed. These approaches can be classified into three categories: in painting- based, multispectral-based, and multitemporal-based. In the first category, without the aid of multispectral and multitemporal data, the cloud-contaminated regions are synthesized using image synthesis and in painting Techniques [4]–[5]. The information inside the cloud contaminated region is synthesized by propagating the geometrical flow inside that region. The synthesis approaches can yield a visually plausible result, which is suitable for cloud free visualization. However, the lack of restoring information of cloud-contaminated pixels makes them unsuitable for further applications. In multispectral-based approaches, multispectral data are utilized in cloud detection and removal [3]–[9]. Rakwatin et al. [3] proposed a reconstruction algorithm to restore missing data of Aqua Moderate Resolution Imaging Spectro radiometer (MODIS) band 6 using histogram matching and least squares fitting. Compared with the multispectral-based approaches, the multitemporal-based approaches [2], [6], [7]–[8] which rely on both temporal coherence and spatial coherence have a better ability to cope with large clouds. Image editing operation is related with global changes such as image correction, filtering, colorization or local changes in a selected region where the altering operations take place. One example of this is the commercial or artistic photomontages that consider the local changes. Along with the technologic improvement in this research topic, quite number of software has been developed for photo editing such as Adobe Photoshop. But, professional experience is required to be able to use these kinds of software skillfully and editing photos using the software takes a long time. Additionally, the edited image regions may include some visible corruptions. In recent years, the image editing methods based on The Poisson equation have been frequently employed [10-11]. An image editing method was presented by Perez et al. based on the Poisson RESEARCH ARTICLE OPEN ACCESS