# An Efficient Encoding Algorithm Using Local Path on Huffman Encoding Algorithm for Compression
## 6 Conclusions  
Encoding algorithms, which are one of the most important steps in each compression algorithm, are studied extensively in the literature. The Huffman and arithmetic coding algorithms are used intensively in this field. The arithmetic coding algorithm has been developed as a more efficient alternative to the Huffman encoding algorithm. Despite its efficiency, the developed arithmetic coding algorithm is relatively slow, complex, and hard to implement. Therefore, a new coding algorithm was needed that is an efficient alternative to the arithmetic coding algorithm, and as fast as (and less complex than) the Huffman encoding algorithm.  
In this paper, we present an alternative encoding algorithm for general compression purposes. The encoding algorithm that we proposed is based on the local path of the Huffman encoding algorithm. The proposed algorithm uses all the advantages offered by the Huffman encoding algorithm, but it also provides solutions to characters that require a long symbol. It also provides similar, or better, results with the arithmetic coding algorithm, which addresses the gaps in the Huffman algorithm. The proposed encoding algorithm also addresses deficiencies in the arithmetic coding algorithm such as implementation difficulties, slow execution times, and unnecessary production of prefix codes.  
Figure 19: NoBPP values of Group 3 images.  
The success of the developed encoding algorithm has been tested on three different groups of images. Some images have similar results with the arithmetic coding algorithm and better compression performances than the Huffman encoding algorithm.  
One of the most important criteria used in evaluating the success of the algorithm is the NoBPP value. From the experiments, we draw the following conclusions:  
1. In Group 1 Images: 1. 2.82% better than the Huffman coding algorithm 2. 2.48% worse than the arithmetic coding algorithm
2. In Group 2 Images 1. 4.33% better than the Huffman coding algorithm 2. 3.96% better than the arithmetic coding algorithm
3. In Group 3 Images 1. 36% better than the Huffman coding algorithm 2. 3.90% better than the arithmetic coding algorithm  
The obtained results show that the developed algorithm has better compression results in a variety of image types. We believe that the proposed algorithm bridges the gaps in the literature because the Huffman tree of the image can have an unbalanced tree structure, the same pixels are as consecutive as possible over the image, and the number of different characters needed was lower in the image.  
Currently we are developing another encoding algorithm model that will improve this encoding algorithm. In the future, we are planning to: (1) develop a dynamic solution in accordance with the 3-bit sequence limit used in this solution, (2) implement a dictionary-based new effective encoding algorithm, and (3) at the end of these objectives, reveal an international architecture of an alternative lossless compression algorithm.  
[PERSON] and [PERSON] conceived and structured the system. [PERSON] and [PERSON] performed literature review, helped in experiments and analyzed the performed data. Both, authors implemented the algorithm, wrote the paper, and read and approved the submitted version of the manuscript.  
This work has been partly supported by the Knrkkale University Department of Scientific Research Projects (2017/084).  
No potential conflict of interest was reported by the authors.