Development of blur detection algorithms has attracted many attentions in recent years. The blur detection algorithms are found very helpful in real life applications and therefore have been developed in various multimedia related research areas including image restoration, image enhancement, and image segmentation. These researches have helped us in compensating some unintentionally blurred images, resulted from out-of-focus objects, extreme light intensity, physical imperfection of camera lenses and motion blur distortion. Overview on a few blur detection methods will be presented in this paper. The methods covered in this manuscript are based on edge sharpness analysis, low depth of field (DOF) image segmentation, blind image de-convolution, Bayes discriminant function method, non-reference (NR) block, lowest directional high frequency energy (for motion blur detection) and wavelet-based histogram with Support Vector Machine (SVM). It is found that there are still a lot of future works need to be done in developing an efficient blur detection algorithm.

Abstract-Animal detection based researches are useful for many real life applications. Animal detection methods are helpful on the research related to locomotive behavioral of targeted animal and also to prevent dangerous animal intrusion in residential area. There are a few branches of research related to animal detection. Therefore, this paper will survey some of these branches.

Detection of blur in digital image, which is commonly preliminary step for de-blurring process, has becoming one of the growing research areas these days and has attracted many attentions from researchers. Research scholars have proposed new methods, or improved blur detection algorithms, based on edge sharpness analysis, low Depth of Field analysis, blind de-convolution, Bayes discriminant function, reference or non-reference block and wavelet based histogram with Support Vector Machine (SVM). The purpose of this paper is to explore the research trends (before year 1993 to year 2012) regarding the usage of blur detection algorithms for digital image processing researches. Because there are thousands of reliable literatures available, the trend is observed from the available online literature alone. Our scope of research has been limited only to search engine of IEEExplore®, ScienceDirect, and Google Scholar database. The searching for literatures will be classified according to their respective keyword for each method being utilized. We observed that low Depth of Field blur detection analysis is currently the most popular method, followed by edge sharpness analysis of blur detection. Google Scholar also has the most abundance source of online literature compared with IEEExplore® and ScienceDirect. Based on the trending graph, we observed that the researches in blur detection method are very positive, showing an overall increasing number of publication from year to year. 

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Abstract-Median filtering is a well known method to deal with impulse noise in digital images. However, due to some limitations associated with the standard median filtering approach, several new improved versions of the median filtering method have been proposed by researchers. The number of methods is expanding from year to year. Therefore, the purpose of this paper is to see the current trend of the median filtering techniques. The trend is observed from the available online literatures; which use or propose new median filtering methods. Because there are thousands of related reliable literatures available online alone, our research concentrates on online literatures only. These literatures were classified according to their search keywords. The scope of our research is limited to IEEExplore®, ScienceDirect, and Google Scholar databases only. The results confirm that the research regarding to median filtering is still growing at this time. Furthermore, we observed that the weighted median filter is the most popular median filtering research, and it is followed by researches on the adaptive median filter.Based on ScienceDirect database, it is shown that all of the median filtering methods showing an increasing number of publications over year.Index Terms-Impulse noise, literature survey, median filtering, salt-and-pepper noise.