A comparative study on improvement of image compression method using hybrid of DCT and DWT techniques with huffman encoding

Image is an important media used to visualize or represent a message in daily conversation between users device. Nowadays, there are many application that involve image processing such as security system, communication system and medical system where images are processed digitally. Image is mainly known for its large data capacity especially high resolution image. Thus, image compression is important to reduce storage size and achieve specific application goals. In this research, hybrid of Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Huffman compression technique is proposed. Stand-alone technique of DCT, DWT and Huffman are execute before hybrid all techniques together. Besides, the performance in determining the quality of image, compression ratio and computing time are carefully observed by evaluating the result of Mean Square Error (MSE), Power Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), compression ratio and time of compression and decompression. It is found that the proposed hybrid technique able to reduce storage size with 3.72:1 compression ratio and short computing time with 5 second. The quality of image is slightly reduce compared to original image which are calculated based on MSE, PSNR and SSIM value with 52.74, 30.92 dB and 0.90, respectively. In conclusion, DWT technique has the ability in compressing image size within short time while DCT and Huffman are able to reduce data loss during compression and maintaining good quality of image. Therefore, DCT, DWT and Huffman method are combined together to support each other in producing good performance

A comparative study on image compression method using stand-alone DWT techniques and hybrid of DWT with huffman coding technique for WSN application

The advent of wireless technologies nowadays gives high impact toward many users to communicate to each other. Wireless Sensor Net-work is a network of nodes which connect to each other by using a device. In addition, transmitting and receiving messages and files are common in most users. There are many platform of network which contributes the same aim that is communication purposes. A ZigBee network is known as one of a platform with its own Standard (IEEE 802.15.4). Unfortunately, ZigBee has a low data rate which limits the capacity of storage in transmitting data. Thus, a large multimedia such as image data are hard to transmit via ZigBee network. Therefore, image compression are necessary in transmission process due to the ability in reducing dimension size and removing redundant image data. In this paper, three method are observed which are stand-alone DWT, stand-alone Huffman, and Hybrid of DWT and Huffman Coding. After conducting a comprehensive observation, it is found that DWT technique are able to compress the image data with less time taken while Huffman technique are suitable in maintaining the quality of image but need a long time to process. Hence, hybrid of DWT with Huffman method are proposed to support each other in terms of compression, computing time and quality of image

A Comparative Study on Improvement of Image Compression Method using Hybrid DCT - DWT Techniques with Huffman Encoding for Wireless Sensor Network Application

Nowadays, the demands on the usage of wireless network are increasing rapidly from year to year. Wireless network is a large scale of area where many nodes are connecting to each other to communicate using a device. Primarily, wireless network also tend to be as a link to transmit and receive any multimedia such as image, sound, video, document and etc. In order to receive the transmitted media correctly, most type of media must be compressed before being transmitted and decompressed after being received by the device or else the device used must have the ability to read the media in a compressed way. In this paper, a hybrid compression of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) with Huffman encoding technique are proposed for Wireless Sensor Network (WSN) application. Data compression is very useful to remove the redundant data and reduce the size of image. After conducting a comprehensive observation, it is found that hybrid compression is suitable due to the process consist of the combination of multiple compression techniques which suits for Wireless Sensor Network’s application focusing on ZigBee platform

Comparative Study on Performance of Discrete Wavelength Transform and Huffman Compression Technique on 2D Signal

Nowadays, the development of technology which involved multimedia data are widely used to help better understanding in spreading information. Image is known as 2D signal which contain huge data especially a high resolution image. In this paper shows the comparison of applying lossy and loss compression on the image data. Image compression is necessary in reducing the size of image for storage or transmission purpose to support most of the application nowadays. Besides, some technique also offers in simplifying the image data to process efficiently. DWT technique and Huffman coding technique are selected as the process of lossy and lossless compression, respectively. The performance of image compression are evaluated in terms of compression ratio, quality of image (MSE, PSNR and SSIM value) and computing time. Several type of evaluation can determine better technique to apply on specific type of application. After conducted a comprehensive observation, DWT technique can provide good performance of compression ratio and computing time as well as the quality of image. Basically, DWT technique only have slight loss of data during the process which the output image is still clear to see by naked eyes. In contrast, Huffman coding technique is lacked in both compression ratio and computing time. However, it helps in maintaining the quality of image without any losses of data. Therefore, certain technique of image compression can be used according to the specific goal of application which depends on the performance of image compression method