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4 articles for “Huffman coding”
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Color Image Compression (Lossy) Through Selective Component Technique and Block Truncation Compression Technique
Abstract: This is a lossy image compression technique, where image is compressed by combination of two individual lossy compression techniques. The first technique is the selective component technique, where any one of the 3 components (R, G, B) is taken in a particular order preserving the colour information of the pixels in lossy manner; and the second technique is the block truncation technique (BTC) applied to the output of the previous …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 1–3 Read article
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Detailed Analysis of Various Data Compression Techniques
Abstract: Data compression refers to reducing the volume of space needed to keep data or reducing the amount of time required to transmit the data. The size of data is diminished by removing the unnecessary information. In this study many different data compression techniques have been studied, such as Shannon Fano, Shannon Fano Elias, Huffman binary and ternary coding. It is found that Huffman coding is the most suitable among these …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 1, 2020 · pp. 1–4 Read article
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Zero Watermarking for Energy Efficiency in Wireless Sensor Networks
Abstract: A group of dedicated and spatially distributed sensors that collect and transmit huge amount of data from the source nodes to the base station (BS) is referred to as Wireless Sensor Networks (WSN). The data is collected from the sensor deployed environment and sent to the BS directly or indirectly (via intermediate nodes). Energy constraint is the key obstacle in WSN by which sensor nodes undergo, where main source of …
Published in Journal of Web Engineering & Technology · Vol. 5, Issue 3, 2018 · pp. 1–9 Read article
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Adaptive Huffman Algorithm for Data Compression Using Text Clustering and Multiple Character Modification
Abstract: Adaptive Huffman algorithm is a popular data compression technique that creates a variable-length binary code for each symbol in a message. However, the original algorithm may not be efficient in compressing text data, particularly when dealing with long sequences of repeated characters. In this study, we propose a novel approach to enhance the compression ratio of the Adaptive Huffman algorithm by utilizing text clustering and multiple character modification. The proposed …
Published in Recent Trends in Programming languages · Vol. 10, Issue 1, 2023 · pp. 30–40 Read article