  Data compression has become a necessity not only the in the field of
communication but also in various scientific experiments. The data that is
being received is more and the processing time required has also become more. A
significant change in the algorithms will help to optimize the processing
speed. With the invention of Technologies like IoT and in technologies like
Machine Learning there is a need to compress data. For example training an
Artificial Neural Network requires a lot of data that should be processed and
trained in small interval of time for which compression will be very helpful.
There is a need to process the data faster and quicker. In this paper we
present a method that reduces the data size. This method is known as Optimized
Huffmans Coding. In the Huffmans coding we encode the messages so as to reduce
the data and here in the optimized Huffmans coding we compress the data to a
great extent which helps in various signal processing algorithms and has
advantages in many applications. Here in this paper we have presented the
Optimized Huffmans Coding method for Text compression. This method but has
advantages over the normal Huffmans coding. This algorithm presented here says
that every letter can be grouped together and encoded which not only reduces
the size but also the Huffmans Tree data that is required for decoding, hence
reducing the data size. This method has huge scientific applications.
