Introduction to Image Blind

What is/are Image Blind?

Image Blind - In order to improve the performance of image deblurring algorithm by increasing the receptive field, an image blind deblurring algorithm based on deep multi-level wavelet transform is proposed. ^[1] A color image blind digital watermarking algorithm based on QR code is proposed. ^[2] Based on similarity images, a nonlocal natural image before the regular term is proposed to deal with the single-image blind deblurring problem. ^[3] In addition, we reconstruct the secret color image by inputting the stego images passing on the decoder which accomplish the secret image blind extraction. ^[4] In this paper, active joint prior learning (JPL) is proposed for real‐world ISAR image blind denoising. ^[5] Single image blind motion deblurring refers to transferring a blurred motion image into a corresponding clear image, which is a challenging and classic problem in the field of computer vision. ^[6] To improve the image quality of the deblurring results restored by existing blind deblurring method, an effective image blind deblurring method based on a single channel and L1-norm is proposed for the blurry images. ^[7] METHODS We proposed a novel end-to-end framework named automatic consecutive context perceived transformer GAN (ACCP-GAN) for fully automatic serial sectioning image blind inpainting. ^[8] Then this paper proposes a color image blind digital watermarking algorithm based on QR code. ^[9] Recently, deep convolutional learning has been applied to image deblurring, which greatly improves the performance of single-image blind deblurring algorithms. ^[10] To maintain a trade-off between robustness and imperceptibility, as well as secure transmission of digital images over communication channels, a digital image blind watermarking scheme on the basis of adaptive neuro-fuzzy inference system (ANFIS) is proposed in this study. ^[11] Blind forensics of JPEG image tampering as a kind of digital image blind forensics technology is gradually becoming a new research hotspot in the field of image security. ^[12] In this paper, we present an end-to-end method for image blind denoising based on a conditional generative adversarial network (GAN). ^[13] Most of the existing single-image blind deblurring methods are tailored for natural images. ^[14] For on-orbit image denoising, we propose an end-to-end trainable image blind denoising network, namely IBDNet. ^[15] In this paper, we propose a novel variational method for single image blind deblurring based on the fractional-order differential, which can overcome the staircase effect produced by the total variation regularization and alleviate the ringing artifact in deblurring. ^[16] This paper aims to propose a candidate solution to the challenging task of single-image blind super-resolution (SR), via extensively exploring the potentials of learning-based SR schemes in the lit. ^[17] This paper deals with the problem of image blind deconvolution in presence of Cauchy noise, a type of non-Gaussian, impulsive degradation which frequently appears in engineering and biomedical applications. ^[18] However, the previous multi-image blind deconvolution methods are prone to inconsistencies between observations such as moving objects, illumination change or mis-alignment. ^[19]

Digital Image Blind

To maintain a trade-off between robustness and imperceptibility, as well as secure transmission of digital images over communication channels, a digital image blind watermarking scheme on the basis of adaptive neuro-fuzzy inference system (ANFIS) is proposed in this study. ^[1] Blind forensics of JPEG image tampering as a kind of digital image blind forensics technology is gradually becoming a new research hotspot in the field of image security. ^[2]

Single Image Blind

Single image blind motion deblurring refers to transferring a blurred motion image into a corresponding clear image, which is a challenging and classic problem in the field of computer vision. ^[1] In this paper, we propose a novel variational method for single image blind deblurring based on the fractional-order differential, which can overcome the staircase effect produced by the total variation regularization and alleviate the ringing artifact in deblurring. ^[2]

Color Image Blind

A color image blind digital watermarking algorithm based on QR code is proposed. ^[1] Then this paper proposes a color image blind digital watermarking algorithm based on QR code. ^[2]

image blind deblurring

In order to improve the performance of image deblurring algorithm by increasing the receptive field, an image blind deblurring algorithm based on deep multi-level wavelet transform is proposed. ^[1] Based on similarity images, a nonlocal natural image before the regular term is proposed to deal with the single-image blind deblurring problem. ^[2] To improve the image quality of the deblurring results restored by existing blind deblurring method, an effective image blind deblurring method based on a single channel and L1-norm is proposed for the blurry images. ^[3] Recently, deep convolutional learning has been applied to image deblurring, which greatly improves the performance of single-image blind deblurring algorithms. ^[4] Most of the existing single-image blind deblurring methods are tailored for natural images. ^[5] In this paper, we propose a novel variational method for single image blind deblurring based on the fractional-order differential, which can overcome the staircase effect produced by the total variation regularization and alleviate the ringing artifact in deblurring. ^[6]

image blind denoising

In this paper, active joint prior learning (JPL) is proposed for real‐world ISAR image blind denoising. ^[1] In this paper, we present an end-to-end method for image blind denoising based on a conditional generative adversarial network (GAN). ^[2] For on-orbit image denoising, we propose an end-to-end trainable image blind denoising network, namely IBDNet. ^[3]

image blind deconvolution

This paper deals with the problem of image blind deconvolution in presence of Cauchy noise, a type of non-Gaussian, impulsive degradation which frequently appears in engineering and biomedical applications. ^[1] However, the previous multi-image blind deconvolution methods are prone to inconsistencies between observations such as moving objects, illumination change or mis-alignment. ^[2]

image blind digital

A color image blind digital watermarking algorithm based on QR code is proposed. ^[1] Then this paper proposes a color image blind digital watermarking algorithm based on QR code. ^[2]