Technological advancements in the scientific world has witnessed its exponential growth since the transformation from analogue to digital devices. Computer Systems transitioned from humongous sized poor performance gadgets to powerful computational devices even surpassing the human intelligence in most scenarios. Such advancements gave birth to algorithmic approach to world most complex problems. As algorithms, for their decision making requires data, which in most cases is in the form of images, those images for the sake for better processing needs to be clear with sharp edges, which simply means there shouldn’t be any kind of blur or noise effecting those input images. Blur or noise are added to the input images during the capturing process either because of the natural scene lighting or the complexity of scene or because of convolution of impulse response which is called as blur kernel or point spread function(PSF). Image processing field which deals with deblurring of such images is called as image restoration. There are two methodologies for dealing with such scenarios that are blind image deblurring and reference based image deblurring. This paper gives extensive review of research done in both domains. Discussing in details the approaches been used along with comparing the data to analyze and specify the methodology that is well suited for most blur scenarios.