Ultrasound Speckle Reduction Based on Histogram Curve Matching and Region Growing

The quality of ultrasound scanning images is usually damaged by speckle noise.This paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing algorithm.Unlike single statistical moment-based speckle reduction algorithms,this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high detectability.The criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in advance.Then,according to the similarity value and tissue characteristics,the entire image is divided into several levels of speckle-content regions,and adaptive smoothing is performed based on these classification characteristics and the corresponding window size determined by the proposed region growing technique.Tests conducted from phantoms and in vivo images have shown very promising results after a quantitative and qualitative comparison with existing work.

Speckle reduction using phase plate array and lens array

In this paper,a solution for speckle reduction using phase plate array(PPA)and lens array(LA)in a motionless way is proposed.The specially designed PPA is composed of sub-phase plates,which are constituted by phase patterns formed by Hadamard sub-matrices.Each component of the proposed optical system should satisfy the stated relationships.The incident laser beam will be incoherent after passing through PPA,and superpose on the screen under the action of LA and main lens.Speckle reduction can be achieved by the averaging of the incoherent speckle patterns.Because of abandoning the mechanical movement,it will be suitable for laser displays and images.

Multi-frame speckle reduction in OCT using supercontinuum pumped by noise-like pulses

In most coherent imaging modality,speckle noise is a major cause that blurs the boundary of tissues and degrades the image contrast.By utilizing the unique properties of supercontinuum(SC)generated by noise-like pulses(NLPs)and a simple multi-frame averaging technique,we achieved significant speckle reduction in spectral domain optical coherence tomography(SD-OCT).We quantitatively compared the speckle of our proposed method with those of conventional swept source OCT(SS-OCT)and SD-OCT based on commercial light sources.The experimental results show that SC pumped by NLPs combined with noncoherent averaging method achieves better denoising performance in terms of contrast to noise ratio(CNR).

Speckle reduction by selective spatial-domain mask in digital holography

An improved method of using a selective spatial-domain mask to reduce speckle noise in digital holography is proposed.The sub-holograms are obtained from the original hologram filtered by the binary masks including a shifting aperture for being reconstructed. Normally, the speckle patterns of these sub-reconstructed images are different. The speckle intensity of the final reconstructed image is suppressed by averaging the favorable sub-reconstructed images which are selected based on the most optimal pixel intensity sub-range in the sub-holograms. Compared with the conventional spatial-domain mask method, the proposed method not only reduces the speckle noise more effectively with fewer sub-reconstructed images,but also reduces the redundant information used in the reconstruction process.

Simultaneous Speckle Reduction and SAR Image Compression Using Multiwavelet Transform

Synthetic aperture radar （SAR） images are corrupted by multiplicative speckle noise which limits the performance of the classical coder/decoder algorithm in spatial domain. The relatively new transform of multiwavelets can possess desirable features simultaneously, such as orthogonality and symmetry, while scalar wavelets cannot. In this paper we propose a compression scheme combining with speckle noise reduction within the multiwavelet framework. Compared with classical set partitioning in hierarchical trees （SPIHT） algorithm, our method achieves favorable peak signal to noise ratio （PSNR） and superior speckle noise reduction performances.

基于塔形形态算法的 SAR图像相干斑抑制(英文)

A Pyramidal Morphology Algorithm is developed for speckle reduction of SARimages in this paper. For reducing the loss of information in the pyramidal algorithm for morphologyprocessing, in this modified algorithm, the sub-images are processed parallel in the downsamplingoperation and the sub-images are reconstructed in the upsampling operation. It can be applied toimage filtering parallel. After analysis the computer simulations show that these two kinds offilters are both effective in speckle reduction of SAR images. The modified parallel algorithm doesbetter than the original algorithm and Lee filter on some characteristics.

Speckle noise reduction in digital holography with spatial light modulator and nonlocal means algorithm

An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Multiple holograms are reconstructed and superimposed, and the intensity is averaged to smooth the noise. The adaptive algorithm based on the nonlocal means is designed to further suppress the speckle. The presented method is compared with other methods reduction is improved, and the proposed method is effective The experimental results show that speckle and feasible.

A Novel Speckle Filter for SAR Images Based on Information-theoretic Heterogeneity Measurements

Most adaptive speckle filters are based on the local coefficient of variation, which serves to measure the heterogeneity of synthetic aperture radar （SAR） images. However, the sensitivity of the measurements to speckle and noise of SAR images would greatly deteriorate the speckle reduction. This article, based upon the information theory, presents a novel parameter for the heterogeneity measurement as a general index to quantitate the SAR image heterogeneity. Further, as a new speckle reduction algorithm based on the aforesaid quantitative heterogeneity measurements, it puts forward a heterogeneity-based speckle reduction filter （HBSRF）, which uses the information-theoretic heterogeneity measurements as a criterion to classify the SAR images as belonging to homogeneous or heterogeneous regions. Then the finite iteration procedure and edge detection algorithms are adopted to strike the best balance between speckle reduction and edge preservation. The results from the computer simulation have demonstrated that the proposed effective method is superior to the conventional speckle filters based on the local coefficient of variation both in textural preservation and speckle reduction.