Henryk Palus | Silesian University of Technology (original) (raw)

Papers by Henryk Palus

Zeszyty Naukowe. Automatyka / Politechnika Śląska, 2000

Przegląd Elektrotechniczny, 2008

Przegląd Elektrotechniczny, 2008

In this paper the postprocessing procedures adapted to the region-based colour image segmentation... more In this paper the postprocessing procedures adapted to the region-based colour image segmentation, represented by unseeded region growing technique, are presented. The removal of small regions from segmented images by merging them to the neighbouring regions with the largest areas was particularly useful. The possibility of using this procedure to removing of highlights that disturbing segmentation process, has been proved. (Postprocessing in region-based colour image segmentation).

Przegląd Elektrotechniczny, 2008

In this paper we show, from image processing point of view, different methods of computing of col... more In this paper we show, from image processing point of view, different methods of computing of colourfulness of the image. We have calculated the colourfulness using simple estimate based on statistical parameters of the pixel cloud along red-green and yellow-blue axes. All experiments have been carried out on the set of natural colour images with different perceptual colourfulness. The relationships between colourfulness of the image and perceptual attributes (H, L, S) of pixels have been experimentally investigated. During image processing the colourfulness of the image can be changed but sometimes it should be preserved e.g. in image filtering. We have presented it on examples, which show that the difference of colourfulness can be useful for evaluating the image filtering algorithms beside such traditional performance functions as PSNR and DeltaE

International Journal of Applied Mathematics and Computer Science, Mar 1, 2011

Proceedings of SPIE, Dec 8, 2015

Color quantization is still an important auxiliary operation in the processing of color images. T... more Color quantization is still an important auxiliary operation in the processing of color images. The K-means clustering (KM), used to quantize the color, requires an appropriate initialization. In this paper, we propose a combined KM method that use to initialize the results of well-known quantization algorithms such as Wu's, NeuQuant (NQ) and Neural Gas (NG). This approach, assessed by three quality indices: PSNR, ΔE and ΔM, improves the results. Experimental results of such combined quantization indicate that the deterministic Wu+KM and random NG+KM approaches leading to the best quantized images.

Proceedings of SPIE, Feb 12, 2015

Image segmentation is one of the most difficult steps in the computer vision process. Pixel clust... more Image segmentation is one of the most difficult steps in the computer vision process. Pixel clustering is only one among many techniques used in image segmentation. In this paper is proposed a new segmentation technique, making clustering in the five-dimensional feature space built from three color components and two spatial coordinates. The advantages of taking into account the information about the image structure in pixel clustering are shown. The proposed 5D k-means technique requires, similarly to other segmentation techniques, an additional postprocessing to eliminate oversegmentation. Our approach is evaluated on different simple and complex images.

Proceedings of SPIE, Mar 17, 2017

Color image quantization is an often used in such tasks as image compression and image segmentati... more Color image quantization is an often used in such tasks as image compression and image segmentation. In the paper, we continue to consider the usefulness of the new DSCSI metric for evaluating quantized images. Our use of the DSCSI metric confirmed that the color quantization in the CIELAB color space is better than in the basic RGB color space. On several examples we found very good DSCSI suitability in the case of quantization with dithering. During the tests of different dithering algorithms the best results, in terms of DSCSI metric, reached the classical Floyd-Steinberg algorithm at error propagation level of 75-85%.

Bulletin of The Polish Academy of Sciences-technical Sciences, 2018

Proceedings of SPIE, Mar 17, 2017

Color quantization is an important operation in the field of color image processing. In this pape... more Color quantization is an important operation in the field of color image processing. In this paper, we consider a usefulness of the new DSCSI metric to assessment of quantized images. This metric is shown in the background of other useful image quality metrics to evaluate the color image differences and it has also been proven that DSCSI metric achieves the highest correlation coefficients with MOS. For further veriffcation DSCSI metric the combined methods that use to initialize the results of well-known splitting algorithms such as POP, MC, Wu etc. were tested. Experimental results of such combined methods indicate that the Wu+KM approach leading to the best quantized images in the sense of DSCSI metric.

Pomiary Automatyka Kontrola, 2007

Breast cancer is one of the most common cancers in women. Typically, the course of the disease is... more Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.

The aim of this work was to test the most popular and essential algorithms of the intensity nonun... more The aim of this work was to test the most popular and essential algorithms of the intensity nonuniformity correction of the breast MRI imaging. In this type of MRI imaging, especially in the proximity of the coil, the signal is strong but also can produce some inhomogeneities. Evaluated methods of signal correction were: N3, N3FCM, N4, Nonparametric, and SPM. For testing purposes, a uniform phantom object was used to obtain test images using breast imaging MRI coil. To quantify the results, two measures were used: integral uniformity and standard deviation. For each algorithm minimum, average and maximum values of both evaluation factors have been calculated using the binary mask created for the phantom. In the result, two methods obtained the lowest values in these measures: N3FCM and N4, however, for the second method visually phantom was the most uniform after correction.

The main goal of colour quantization methods is a colour reduction with minimum colour error. In ... more The main goal of colour quantization methods is a colour reduction with minimum colour error. In this paper were investigated six following colour quantization techniques: the classical median cut, improved median cut, clustering k-means technique in two colour versions (RGB, CIELAB) and also two versions of relative novel technique named k-harmonic means. The comparison presented here was based on testing of ten natural colour images for quantization into 16, 64 and 256 colours. In evaluation process two criteria were used: the mean squared quantization error (MSE) and the average error in the CIELAB colour space (DeltaE). During tests the efficiency of k-harmonic means applied to colour quantization has been proved.

Zeszyty Naukowe. Automatyka / Politechnika Śląska, 2000

Przegląd Elektrotechniczny, 2008

Przegląd Elektrotechniczny, 2008

In this paper the postprocessing procedures adapted to the region-based colour image segmentation... more In this paper the postprocessing procedures adapted to the region-based colour image segmentation, represented by unseeded region growing technique, are presented. The removal of small regions from segmented images by merging them to the neighbouring regions with the largest areas was particularly useful. The possibility of using this procedure to removing of highlights that disturbing segmentation process, has been proved. (Postprocessing in region-based colour image segmentation).

Przegląd Elektrotechniczny, 2008

In this paper we show, from image processing point of view, different methods of computing of col... more In this paper we show, from image processing point of view, different methods of computing of colourfulness of the image. We have calculated the colourfulness using simple estimate based on statistical parameters of the pixel cloud along red-green and yellow-blue axes. All experiments have been carried out on the set of natural colour images with different perceptual colourfulness. The relationships between colourfulness of the image and perceptual attributes (H, L, S) of pixels have been experimentally investigated. During image processing the colourfulness of the image can be changed but sometimes it should be preserved e.g. in image filtering. We have presented it on examples, which show that the difference of colourfulness can be useful for evaluating the image filtering algorithms beside such traditional performance functions as PSNR and DeltaE

International Journal of Applied Mathematics and Computer Science, Mar 1, 2011

Proceedings of SPIE, Dec 8, 2015

Color quantization is still an important auxiliary operation in the processing of color images. T... more Color quantization is still an important auxiliary operation in the processing of color images. The K-means clustering (KM), used to quantize the color, requires an appropriate initialization. In this paper, we propose a combined KM method that use to initialize the results of well-known quantization algorithms such as Wu's, NeuQuant (NQ) and Neural Gas (NG). This approach, assessed by three quality indices: PSNR, ΔE and ΔM, improves the results. Experimental results of such combined quantization indicate that the deterministic Wu+KM and random NG+KM approaches leading to the best quantized images.

Proceedings of SPIE, Feb 12, 2015

Image segmentation is one of the most difficult steps in the computer vision process. Pixel clust... more Image segmentation is one of the most difficult steps in the computer vision process. Pixel clustering is only one among many techniques used in image segmentation. In this paper is proposed a new segmentation technique, making clustering in the five-dimensional feature space built from three color components and two spatial coordinates. The advantages of taking into account the information about the image structure in pixel clustering are shown. The proposed 5D k-means technique requires, similarly to other segmentation techniques, an additional postprocessing to eliminate oversegmentation. Our approach is evaluated on different simple and complex images.

Proceedings of SPIE, Mar 17, 2017

Color image quantization is an often used in such tasks as image compression and image segmentati... more Color image quantization is an often used in such tasks as image compression and image segmentation. In the paper, we continue to consider the usefulness of the new DSCSI metric for evaluating quantized images. Our use of the DSCSI metric confirmed that the color quantization in the CIELAB color space is better than in the basic RGB color space. On several examples we found very good DSCSI suitability in the case of quantization with dithering. During the tests of different dithering algorithms the best results, in terms of DSCSI metric, reached the classical Floyd-Steinberg algorithm at error propagation level of 75-85%.

Bulletin of The Polish Academy of Sciences-technical Sciences, 2018

Proceedings of SPIE, Mar 17, 2017

Color quantization is an important operation in the field of color image processing. In this pape... more Color quantization is an important operation in the field of color image processing. In this paper, we consider a usefulness of the new DSCSI metric to assessment of quantized images. This metric is shown in the background of other useful image quality metrics to evaluate the color image differences and it has also been proven that DSCSI metric achieves the highest correlation coefficients with MOS. For further veriffcation DSCSI metric the combined methods that use to initialize the results of well-known splitting algorithms such as POP, MC, Wu etc. were tested. Experimental results of such combined methods indicate that the Wu+KM approach leading to the best quantized images in the sense of DSCSI metric.

Pomiary Automatyka Kontrola, 2007

Breast cancer is one of the most common cancers in women. Typically, the course of the disease is... more Breast cancer is one of the most common cancers in women. Typically, the course of the disease is asymptomatic in the early stages of breast cancer. Imaging breast examinations allow early detection of the cancer, which is associated with increased chances of a complete cure. There are many breast imaging techniques such as: mammography (MM), ultrasound imaging (US), positron-emission tomography (PET), computed tomography (CT), and magnetic resonance imaging (MRI). These imaging techniques differ in terms of effectiveness, price, type of physical phenomenon, the impact on the patient and its availability. In this paper, we focus on MRI imaging and we compare three breast lesion segmentation algorithms that have been tested on QIN Breast DCE-MRI database, which is publicly available. The obtained values of Dice and Jaccard indices indicate the segmentation using k-means algorithm.

The aim of this work was to test the most popular and essential algorithms of the intensity nonun... more The aim of this work was to test the most popular and essential algorithms of the intensity nonuniformity correction of the breast MRI imaging. In this type of MRI imaging, especially in the proximity of the coil, the signal is strong but also can produce some inhomogeneities. Evaluated methods of signal correction were: N3, N3FCM, N4, Nonparametric, and SPM. For testing purposes, a uniform phantom object was used to obtain test images using breast imaging MRI coil. To quantify the results, two measures were used: integral uniformity and standard deviation. For each algorithm minimum, average and maximum values of both evaluation factors have been calculated using the binary mask created for the phantom. In the result, two methods obtained the lowest values in these measures: N3FCM and N4, however, for the second method visually phantom was the most uniform after correction.

The main goal of colour quantization methods is a colour reduction with minimum colour error. In ... more The main goal of colour quantization methods is a colour reduction with minimum colour error. In this paper were investigated six following colour quantization techniques: the classical median cut, improved median cut, clustering k-means technique in two colour versions (RGB, CIELAB) and also two versions of relative novel technique named k-harmonic means. The comparison presented here was based on testing of ten natural colour images for quantization into 16, 64 and 256 colours. In evaluation process two criteria were used: the mean squared quantization error (MSE) and the average error in the CIELAB colour space (DeltaE). During tests the efficiency of k-harmonic means applied to colour quantization has been proved.