Suhaila Sari

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In many practical cases of image processing, only a noisy image is available. Many image denoising methods usually require the exact value of the noise distribution as an essential filter parameter. However, to estimate the noise solely from the information of the noisy image is a difficult task. A simple but accurate noise estimator would significantly(More)
In this paper, we propose a new image compression scheme that is based on the wavelet transform. The image is first divided into 64 × 64 pixels block. The progressive pixel-to-pixel evaluation is done to find the individual pixel intensity in each block. Then the different value between the maximum pixel intensity value and the minimum pixel(More)
Filtering process is important to make sure the resultant image is free from noise. This paper introduces a new filtering technique for optical tomography to reduce the noise or called a smearing effect. With this technique, it also can increase the Peak Signal to Noise Ratio (PSNR). This smearing effect is resultant from Linear Back Projection (LBP)(More)
This paper proposes a method to estimate the wavelet coefficient threshold value at wavelet details subbands to archive high quality image compression. It uses the features of Discrete Wavelet Transform (DWT) where the images are decomposed into one approximate subband and three detail subbands. The detail subbands consists of Diagonal, Vertical and(More)
A good noise reduction is a method that can reduce the noise level and preserve the details of the image. This paper proposes the development of a denoising method through hybridization of bilateral filters and wavelet thresholding for digital images in low light condition.In the first stage, the noisy image is passed through Bilateral Filter. However, only(More)
Nowadays, ultrasound image is important and very useful in medical field. It is a technique used for visualizing body structures including tendons, muscles, joints, vessels and internal organs. However, it will cause some problem if the method of edge detection is not suitable. It can affect the visual diagnosis of medical personnel. Edge detection is(More)
In this paper, a new thresholding algorithm that can distinguish between significant and non-significant coefficient at each detail subbands using standard deviation-based wavelet coefficients threshold estimation is proposed. The proposed algorithm start with calculating the threshold value by using the proposed threshold value estimator at wavelet detail(More)
The process before quantization stage in compression process is a very crucial stage espeacially in application that require a high compression ratios. So, in this paper, we propose a new method of image compression that is based on reducing the wavelet coefficients in wavelet details subbands. It is based on the concept of local subband wavelet(More)
Nowadays, compressed image is a very useful way to transfer or store data because of its smaller size in comparison to the original image. However, if the compression ratio is high, the produced image may be corrupted by blocky artifacts. In many applications that require only the detection of the image edges, it is difficult to distinguish the edges, fine(More)
This research emphasis on problem of quantization process in transform-based image compression. In specifying the quantizer, the size of interval is giving huge impact to the quantization performance. Generally, high quantization error will occurred if large interval is used at high difference value bin. Thus, quantizer needs to be design carefully to(More)
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