Effective image enhancement using hybrid multi resolution image fusion

Image fusion plays an important role in image enhancement and retrieval. For multi-focus image fusion as it is related to frequency distortion the wavelet with symmetric property is more useful to retrieve the image. Hence, to select the wavelet family, which provides better frequency resolution is of immense importance. Due to this property of haar and biorthogonal wavelet bases, they are used for multi focus image fusion. Spatial frequency measures the overall activity level in an image. Some abrupt spatial changes in the image are represented by the high spatial frequencies in the image like edges. Edges are the salient features of an image which gives the information about the fine details. Low spatial frequencies, on the other hand, represents global information about the shape and the orientation of an image. Due to this spatial frequency is used as the feature of selection. A novel hybrid approach to multi-focus image fusion is used. Wavelet coefficients of both the source images are combined by applying different fusion rules for low and high frequency coefficients. Applied a Laplacian pyramid based transform onto the low frequency coefficients of both the input images. For coefficient selection applied a maximum selection fusion rule. High frequency coefficients are selected based upon maximum spatial frequency. The presented algorithm is compared with those of the individual fusion methods. The better result obtained with the combined method (proposed) as compared to the individual methods. The statistical analysis is performed using reference and non reference based metrics. Important feature based metrics are considered.