Reducing the Computation Complexity of 2-D Gaussian Filter

Now a day’s we are facing a problem regarding smoothing of the image.One of the very
useful method to smoothing the image is 2-D Gaussian Filter, which is used in Image Processing.
However, the heavy computational resources are required by 2-D Gaussian Filter, and it comes down to
real-time applications. The vital efficiency is achieved in this implementation. We use floating-point
representation, but there are certain obstacle for this implementation because it requires large
computational power in order to achieve real-time image processing. On the other hand a fixed-point
approach is much more suitable for the implementation of a 2-D Gaussian filter in FPGA.By using
fixed-point arithmetic for the implementation, the efficiency is increases, size of area decreases,
complexity decreases and the computational cost is also reduced.In this paper we reduced the LUT by
11.34 % by using Gaussian filter.