Efficient quantum image representation and compression circuit using zero-discarded state preparation approach

06/22/2023
by   Md Ershadul Haque, et al.
0

Quantum image computing draws a lot of attention due to storing and processing image data faster than classical. With increasing the image size, the number of connections also increases, leading to the circuit complex. Therefore, efficient quantum image representation and compression issues are still challenging. The encoding of images for representation and compression in quantum systems is different from classical ones. In quantum, encoding of position is more concerned which is the major difference from the classical. In this paper, a novel zero-discarded state connection novel enhance quantum representation (ZSCNEQR) approach is introduced to reduce complexity further by discarding '0' in the location representation information. In the control operational gate, only input '1' contribute to its output thus, discarding zero makes the proposed ZSCNEQR circuit more efficient. The proposed ZSCNEQR approach significantly reduced the required bit for both representation and compression. The proposed method requires 11.76% less qubits compared to the recent existing method. The results show that the proposed approach is highly effective for representing and compressing images compared to the two relevant existing methods in terms of rate-distortion performance.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/14/2022

A novel state connection strategy for quantum computing to represent and compress digital images

Quantum image processing draws a lot of attention due to faster data com...
research
08/30/2022

Advance quantum image representation and compression using DCTEFRQI approach

In recent year, quantum image processing got a lot of attention in the f...
research
10/08/2021

Quantum pixel representations and compression for N-dimensional images

We introduce a novel and uniform framework for quantum pixel representat...
research
04/04/2022

Continuous Variable Quantum MNIST Classifiers

In this paper, classical and continuous variable (CV) quantum neural net...
research
01/31/2018

QRMW: Quantum representation of multi wavelength images

In this study, we propose quantum representation of multi wavelength ima...
research
05/06/2022

Incremental Data-Uploading for Full-Quantum Classification

The data representation in a machine-learning model strongly influences ...
research
05/10/2023

Novel Quantum Information Processing Methods and Investigation

Quantum information processing and its subfield, quantum image processin...

Please sign up or login with your details

Forgot password? Click here to reset