Discrete Wavelet Transform Compression Research Articles

Cross-Channel Color Image Encryption Scheme Based on Discrete Memristive Coupled Neurons and DWT Compression

To address the consumption and security of color images for transmission and storage, a cross-channel color image encryption scheme based on a discrete memristive coupled neuron model and DWT compression is designed in this article. Firstly, the dynamics of the discrete memristive coupled neuron system are analyzed and found to possess the hyperchaotic phenomenon, which provides sufficient security for the encryption scheme. Secondly, the color image processed by discrete wavelet transform (DWT) has a quarter of the previous capacity. Then, the color image is combined with a Hash function, and the resulting Hash sequence is given the initial value of the hyperchaotic system. Next, a particle swarm foraging algorithm (PSFA) is designed to better disrupt the correlation in the RGB channel. Finally, a complementary DNA coding rule is implemented for the further encryption of color images. Simulation results show that even with DWT lossy compression, the recovered image can be clearly seen. The performance analysis illustrates that under the hyperchaotic system, the proposed encryption algorithm brings higher security for color images.

Event-Driven ECG Sensor in Healthcare Devices for Data Transfer Optimization

The long-term monitoring of cardiovascular signs requires a wearable and connected electrocardiogram (ECG) healthcare device. It increases user’s comfort and diagnosis quality of chronic cardiac and/or high-risk patients. This paper covers the enormous data to be transmitted from the ECG device to the physician’s, namely the cardiologist’s, control unit. Existent ECG devices uniformly sample analog signals and convert them to digital samples which are compressed before data transmission. However, event-driven sampling simultaneously compresses and samples. Therefore, this paper quantitatively compares successive approximation register analog-to-digital converter (SAR ADC) with discrete wavelet transform (DWT) compression and level-crossing analog-to-digital converter (LC-ADC). Evaluation metrics are the percent root-mean-square difference ( {text{PRD}} ), bit compression ratio ( {text{BCR}} ) and data length in bits. When a 12-bit reconstruction is operated on the outputs of an 8-bit LC-ADC with 12-bit and 10-kHz reference counter, the {text{BCR}} is equal to 80% for 75% of test ECG signals. That is better than the 71.87% {text{BCR}} of the 12-bit 1-kHz SAR ADC with DWT compression. The modeled LC-ADC guarantees a signal quality in terms of {text{PRD}} comparable to the {text{PRD}} of the SAR ADC with DWT compression. The data length in bits of the LC-ADC is lower than the data length in bits of the SAR ADC with more than 14-bit resolution with DWT compression for 82% of the test ECG signals. However, for lower resolutions, to obtain lower power consumption for radiofrequency transmission, a better alternative remains the SAR ADC with DWT compression.

Enhancement of Satellite Image Compression Using a Hybrid (DWT–DCT) Algorithm

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT–DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT–DCT) method to enhance the image compression process on-board satellites.

Optical Emission Spectrum Processing Using Wavelet Compression During Wafer Fabrication

This paper describes the application of discrete-wavelet transform (DWT)-based algorithms to compress optical emission spectral intensity data collected during wafer fabrication. The major goal is to seek computationally efficient compression algorithms that can significantly reduce the data storage requirement but also are capable of retaining enough data authenticity critical for diagnostic purposes. The potential benefits will provide a promising foundation for an integrated data collection and compression tool. The optical emission data are treated in this paper either as images for the whole spectrum or bands of time series and are treated accordingly using appropriate DWT compression approaches. We have found through representative simulation examples that using the set partitioning in hierarchical trees compression algorithm it is achievable to obtain better than 99% storage reduction for optical emission spectrum (OES) images. For OES time series we have achieved around 95% storage reduction with Daubechies and Haar wavelets. The storage reductions are achieved while maintaining sufficient authenticity to retain the dynamic nature of OES data for diagnostic purposes.