Creating panoramic images has become a popular feature in modern smart phones, tablets, and digital cameras. A user can create a 360 degree field-of-view photograph from only several images. Quality of the resulting image is related to the number of source images, their brightness, and the used algorithm for their stitching and blending. One of the algorithms that provides excellent results in terms of background color uniformity and reduction of ghosting artifacts is the multi-band blending. The algorithm relies on decomposition of image into multiple frequency bands using dyadic filter bank. Hence, the results are also highly dependant on the used filter bank. In this paper we analyze performance of the FIR filters used for multi-band blending. We present a set of five filters that showed the best results in both literature and our experiments. The set includes Gaussian filter, biorthogonal wavelets, and custom-designed maximally flat and equiripple FIR filters. The presented results of filter comparison are based on several no-reference metrics for image quality. We conclude that 5/3 biorthogonal wavelet produces the best result in average, especially when its short length is considered. Furthermore, we propose a real-time FPGA implementation of the blending algorithm, using 2D non-separable systolic filtering scheme. Its pipeline architecture does not require hardware multipliers and it is able to achieve very high operating frequencies. The implemented system is able to process 91 fps for 1080p (1920 x 1080) image resolution.