Skip to content
naulon
Not checkedNot checked for notices yet.

Image Enhancement and Features Extraction of Electron Microscopic Images Using Sigmoid Function and 2D-DCT

Vivek Arya, Hemant Choubey, Sandeep Sharma and 2 more

IEEE Access · 2022

doi:10.1109/access.2022.3192416 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

An innovative image enhancement and feature extraction technique that is based on the modified sigmoid function and two-dimensional DCT has been developed. The proposed technique uses a modified sigmoid function that accommodates the original microscopic input image characteristics. A novel block-based input value coupled with the modified sigmoid function is used in this proposed technique to provide good contrast enhancement of an image, resulting in localised contrast enhancement. Singular value decomposition played an important role after DCT because the singular value matrix determines the intensity values of the provided microscopic image. Changes in the singular values have an immediate impact on the intensity of the microscopic input image. The proposed methodology essentially converts the input picture into the SVD-DCT domain, normalises the singular value matrix, and finally reconstructs the enhanced image using inverse DCT. Simulation findings demonstrate that the proposed technique produces significantly superior improved results compared to other current approaches. Various essential characteristics of actinomycetes become evident once electron microscopic images are enhanced, such as long filaments, coils or spirals, rod shapes, and spore patterns. The presented method works successfully and efficiently for various bright and dark microscopic images.

Abstract licence: CC BY-NC-ND

References33

    33 more references, whose wording the paper’s licence keeps private.

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.