Ahmad Kadri Junoh
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Preferred name
Ahmad Kadri Junoh
Official Name
Ahmad Kadri, Junoh
Alternative Name
Junoh, Ahmad Kadri
Junoh, A. K.
Ahmad Kadri, Junoh
Junoh, A. K.
Kadri, J. Ahmad
Main Affiliation
Scopus Author ID
38561331300
Researcher ID
FZU-4175-2022

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  • Publication
    An overview of multi-filters for eliminating impulse noise for digital images
    ( 2020-02-01)
    Abdurrazzaq A.
    ;
    Ahmad Kadri Junoh
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Zainab Yahya
    ;
    Mohd I.
    An image through the digitization process is referred to as a digital image. The quality of the digital image may be degenerating due to interferences on the acquisition, transmission, extraction, etc. This attracted the attention of many researchers to study the causes of damage to the information in the image. In addition to finding cause of image damage, the researchers also looking for ways to overcome this problem. There are many filtering techniques that have been introduced to deal the damage to the information in the image. In addition to eliminating noise from the image, filtering techniques also aims to maintain the originality of the features in the image. Among the many research papers on image filtering there is a lack of review papers which are an important to facilitate researchers in understanding the differences in each filtering technique. Additionally, it helps researchers determine the direction of research conducted based on the results of previous research. Therefore, this paper presents a review of several filtering techniques that have been developed so far.
  • Publication
    Tropical algebra based adaptive filter for noise removal in digital image
    ( 2020-07-01)
    Abdurrazzaq A.
    ;
    Mohd I.
    ;
    Ahmad Kadri Junoh
    ;
    Zainab Yahya
    The concept of the tropical algebra was first introduced to solve problems in mathematical economy such as optimization and approximation problems. In this paper, the concept of tropical algebra is used to build an image filtering algorithm. By using this concept, the lowest and highest pixel values are considered in determining the new pixel value. In addition, adaptive window will also be implemented to help the filtering process become more effective at high density noise. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) are used to evaluate the output image quality produced by the filtering method. In this experiment, the performance of proposed method and existing methods such as switching median filter (SMF), adaptive fuzzy noise switching median filter (NAFSM), modified decision based on unsymmetric trimmed median filter (MDBUTMF), adaptive type-2 fuzzy filter (AT2FF)), based on pixel density filters (BPDF), different applied median filters (DAMF), and tropical SVD filters (TSVD) will be compared. PSNR and SSIM results show that the proposed method outperforms most existing methods: SMF (27.13/0.7954), NAFSM (29.11/0.8459), MDBTUMF (29.18/0.8462), AT2FF (28.10/0.8159), BPDF (25.65/0.7545), DAMF (31.20/0.8833), TSVD (28.39/0.7906), and proposed (31.26/0.8827).
  • Publication
    New white blood cell detection technique by using singular value decomposition concept: White blood cell detection technique
    ( 2021-01-01)
    Abdurrazzaq A.
    ;
    Ahmad Kadri Junoh
    ;
    Zainab Yahya
    ;
    Mohd I.
    Segmentation technique is a commonly used method to detect white blood cells. The segmentation technique aims to separate the blood image into several parts based on the similarity of features in the image. Therefore, the detection results do not completely contain white blood cells but also contain other parts with similar features to white blood cells. This study proposes a new detection technique that directly considers the features of white blood cells using singular value decomposition approach. The experimental results show that the proposed method works better in detecting white blood cell nuclei than the existing methods. The existing methods only work well for white blood cells with dense color intensities such as basophil and monocyte. Meanwhile, the proposed method works well overall as it directly compares the level of similarity in white blood cells.
  • Publication
    Hybrid singular value decomposition based alpha trimmed mean-median filter in eliminating high density salt and pepper noise from grayscale image
    ( 2024-07-01)
    Zain M.S.M.
    ;
    Ahmad Kadri Junoh
    ;
    Abdurrazzaq A.
    The use of images has increased over the previous decade and they have the potential to be effective communication tools, similar to social media. In this technological era, uploading information or visual images to the social media seems to be gaining popularity lately. Therefore, a good image is important to provide the right information. However, the information in the image can be lost or corrupted due to the appearance of noise caused by the digitization, transmission or acquisition process. Thus, it is necessary to remove the noise before using the image for subsequent task. In this study, a new method for removing salt and pepper noise in digital image is proposed by using singular value decomposition and alpha trimmed mean median approach. The singular value decomposition will be used in the detection process by considering the distribution of pixel values in the processed image. Next, the detected noisy pixels will be replaced with a new value obtained from the trimmed alpha mean median approach. The experimental process was performed on a grayscale image with a resolution of 512×512 prepared with a salt and pepper noise density varying between 10% to 90% in order to compare the proposed method to other existing methods. The experimental results show that the proposed method has successfully reduced salt and pepper noise in high noise density. In addition, the proposed method provides better filtering results in terms of visual effects and quantitative measurement results compared to the several existing methods.
      1
  • Publication
    A new denoising method for removing salt & pepper noise from image
    ( 2022-01-01)
    Charmouti B.
    ;
    Ahmad Kadri Junoh
    ;
    Abdurrazzaq A.
    ;
    Mohd Yusoff Mashor
    Digital image has a significant importance in many fields in human life such as, in medicine, photography, biology, astronomy, industry and defense. Thus, it attracts the attention of large number of researchers, among them those interested in preserving the image features from any factors that may reduce the image quality. One of these factors is the noise. Thus far, solving this noise problem remains a challenge point for the researchers in this field, a huge number of image denoising techniques have been introduced in order to remove the noise with taking care of the image features (edges, sharpness). However, besides that, the findings proved to be inconclusive yet. From this point, the current paper aims to introduce a new denoising method for removing salt & pepper noise from the digital image through spatial way. This denoising method exploits the relationship between pixel’s values when the image changes color. Which gives ordered sequences of values in the four directions, horizontal, vertical and diagonals of the window. The proposed method relays on this concept to change the corrupted pixel, by using the neighbors in the window to extracts the truest value (subjects to this sequence) of the treated pixel. This method has been proven to be simple, effective and performing well comparing with the existing restoration methods with low computational cost.
      1