Image compression—from DCT to wavelets

Saha, S.

doi:10.1145/331624.331630

Cited by 106 publications

(54 citation statements)

References 17 publications

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“…Diamond Encoding improved the capacity which is further enhanced by Adaptive Pixel Pair Matching [12]. Adaptive Pixel Triplet Matching improved the effective capacity even more by using three pixels as an embedding unit [13].…”

Section: Literature Surveymentioning

confidence: 99%

Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary

Rajan¹,

Sunder²

2017

IJIVP

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Digital image steganography is an emerging technique in secure communication for the modern connected world. It protects the content of the message without arousing suspicion in a passive observer. A novel steganography method is presented to hide text in digital images. A compact dictionary is designed to efficiently communicate all types of secret messages. The sorting order of pixels in image blocks are chosen as the carrier of embedded information. The high correlation in image pixel values means reordering within image blocks do not cause high distortion. The image is divided into blocks and perturbed to create non repeating sequences of intensity values. These values are then sorted according to the message. At the receiver end, the message is read from the sorting order of the pixels in image blocks. Only those image blocks with standard deviation lesser than a given threshold are chosen for embedding to alleviate visual distortion. Information Security is provided by shuffling the dictionary according to a shared key. Experimental Results and Analysis show that the method is capable of hiding text with more than 4000 words in a 512×512 grayscale image with a peak signal to noise ratio above 40 decibels.

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Section: Literature Surveymentioning

confidence: 99%

Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary

Rajan¹,

Sunder²

2017

IJIVP

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“…After all, there is no need to block of the original image and its basis method have a variable length, wavelet based coding methods can abstain blocking artifacts. The wavelet coding also inclusion to the extended communication of images [13]. Uncertainly the researchers target on Discrete Wavelet Compression Technique.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Despite, the tiling of the blocks motivates blocking artifacts downfall the performance, specifically at minimum bit rates [13] [15]. …”

Section: Discrete Cosine Transformmentioning

confidence: 99%

Improved Wavelet Compression Algorithm for Color Image

Babu¹,

Perumal²,

Kumar³

2017

IJIVP

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An image compression technique has been done in research in the recent years due to its clarity and quality compared to other techniques. Image compression based on wavelet is very important-role and occupies many applications. The objective of image compression is to help in storing the transmitted date in an efficient way by decreasing its redundancy. The wavelet compression reduces the size of the image data while retaining information and maintaining a certain wavelet compression. The proposed method of Improved Wavelet Compression (IWC) is presented in this paper. The proposed IWC gets a color image from the database. After receiving image, waveletTransformation using filter bank techniques are applied to the test image. After compression, the inverse IWC decompression algorithm receives compressed image and applied decompression technique. The image is generated and image quality is reconstructed and the original image is evaluated. The numerical measure parameters such as MSE, PSNR, are used to compare various images. From the experimental result, it is observed that the proposed method IWC gives a better compression ratio in 64.56 while compared to the existing methods.

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“…These coefficients will no longer be correlated across different input sequences, as they can otherwise be compressed further [96]. Next, this smaller set of significant coefficients is encoded in a way that allows reconstruction of an approximation to those coefficients [94]. The process is simply reversed to decode an approximation to the original data.…”

Section: Scalar Environmental Datamentioning

confidence: 99%

Progressively communicating rich telemetry from autonomous underwater vehicles via relays

Murphy¹

2012

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As analysis of imagery and environmental data plays a greater role in mission construction and execution, there is an increasing need for autonomous marine vehicles to transmit this data to the surface. Without access to the data acquired by a vehicle, surface operators cannot fully understand the state of the mission. Communicating imagery and high-resolution sensor readings to surface observers remains a significant challenge -as a result, current telemetry from free-roaming autonomous marine vehicles remains limited to 'heartbeat' status messages, with minimal scientific data available until after recovery. Increasing the challenge, longdistance communication may require relaying data across multiple acoustic hops between vehicles, yet fixed infrastructure is not always appropriate or possible.In this thesis I present an analysis of the unique considerations facing telemetry systems for free-roaming Autonomous Underwater Vehicles (AUVs) used in exploration. These considerations include high-cost vehicle nodes with persistent storage and significant computation capabilities, combined with human surface operators monitoring each node. I then propose mechanisms for interactive, progressive communication of data across multiple acoustic hops. These mechanisms include wavelet-based embedded coding methods, and a novel image compression scheme based on texture classification and synthesis. The specific characteristics of underwater communication channels, including high latency, intermittent communication, the lack of instantaneous end-to-end connectivity, and a broadcast medium, inform these proposals. Human feedback is incorporated by allowing operators to identify segments of data that warrant higher quality refinement, ensuring efficient use of limited throughput. I then analyze the performance of these mechanisms relative to current practices.Finally, I present CAPTURE, a telemetry architecture that builds on this analysis. CAPTURE draws on advances in compression and delay tolerant networking to enable progressive transmission of scientific data, including imagery, across mul-3 tiple acoustic hops. In concert with a physical layer, CAPTURE provides an endto-end networking solution for communicating science data from autonomous marine vehicles. Automatically selected imagery, sonar, and time-series sensor data are progressively transmitted across multiple hops to surface operators. Human operators can request arbitrarily high-quality refinement of any resource, up to an error-free reconstruction. The components of this system are then demonstrated through three field trials in diverse environments on SeaBED, OceanServer and Bluefin AUVs, each in different software architectures.

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Image compression—from DCT to wavelets

Cited by 106 publications

References 17 publications

Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary

Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary

Improved Wavelet Compression Algorithm for Color Image

Progressively communicating rich telemetry from autonomous underwater vehicles via relays

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