Image File Size Research Articles

Adaptive deduplication of virtual machine images using AKKA stream to accelerate live migration process in cloud environment

Cloud Computing is a paradigm which provides resources to users from its pool based on demand to satisfy their requirements. During this process, many servers are overloaded and underloaded in the cloud environment. Thus, power consumption and load balancing are the major problems and are resolved by live virtual machine (VM) migration. Load balancing is addressed by moving virtual machines from overloaded host to under loaded host and from under loaded host to any other host which is not overloaded called VM migration. If this process is done without power off (Live) the virtual machines then it is called live VM migration. By this process, the issue of power consumption by physical hosts is also resolved. Migrating virtual machines involves virtualized components like storage disks, memory, CPU and networking, the entire state of VM is captured as a collection of data files. These data files are virtual disk files, configuration files, and log files. The virtual disk files take larger memory and take more migration time and hence the downtime. These disk files include many zero pages, similar and redundant pages. Many techniques such as compression, deduplication is used reduce the size of VM disk image file. Compression techniques are not widely used, due to the disadvantage of compression ratio and decompression time. Many researchers hence used deduplication techniques for reducing the VM disk image file in the live migration process. The significance of the research work is to design an adaptive deduplication mechanism for reducing VM disk image file size by performing fixed length and variable length block-level deduplication processes. The Rabin-Karp rolling hash algorithm is used in variable length block-level deduplication. Akka stream is used for streaming the VM disk image files as it is the bulk volume of live data transfer. To reduce the time of the deduplication process, many researchers used multithreading and multi-core technologies. We use multithreading in Akka framework to run the deduplication process concurrently without OutofMemory errors. The experiment results show that we achieved a maximum of 83% overall reduction in image storage space and 89.76% reduction in total migration time are achieved by adaptive deduplication method. 3% improvement in deduplication rate when compared with the existing image management system. The results are significant because when we apply this in the storage of data centres, there are much space savings. The reduction in size is dependent on the dataset was taken and the applications running on the VM.

DWT Based Image Compression for Health Systems

There are calls for enhancing present healthcare sectors when it comes to handling huge data size of patients’ records. The huge files contain lots of duplicate copies. Therefore, the ideal of compression comes into play. Image data compression removes redundant copies (multiple unnecessary copies) that increase the storage space and transmission bandwidth. Image data compression is pivotal as it helps reduce image file size and speeds up file transmission rate over the internet through multiple wavelet analytics methods without loss in the transmitted medical image data. Therefore this report presents data compression implementation for healthcare systems using a proposed scheme of discrete wavelet transform (DWT), Fourier transform (FT) and Fast Fourier transform with capacity of compressing and recovering medical image data without data loss. Healthcare images such as those of human heart and brain need fast transmission for reliable and efficient result. Using DWT which has optimal reconstruction quality greatly improves compression. A representation of enabling innovations in communication technologies with big data for health monitoring is achievable through effective data compression techniques. Our experimental implementation shows that using Haar wavelet with parametric determination of MSE and PSNR solve our aims. Many imaging techniques were also deployed to further ascertain DWT method’s efficiency such as image compression and image de-noising. The proposed compression of medical image was excellent. It is essential to reduce the size of data sets by employing compression procedures to shrink storage space, reduce transmission rate, and limit massive energy usage in health monitoring systems. The motivation for this work was to implement compression method to modify traditional healthcare platform to lower file size, and reduce cost of operation. Image compression aims at reconstructing images from extensively lesser estimations than were already thought necessary in relations with non-zero coefficients. Rationally, fewer well-chosen interpretations is adequate to reproduce the new sample exactly as the source image. We look at DWT to implement our compression method.

A reversible data hiding scheme for JPEG images by doubling small quantized AC coefficients

Reversible data hiding for Joint Photographic Experts Group (JPEG) images has become popular in recent years, since JPEG images are widely used in practical applications. An improved reversible data hiding (RDH) method for JPEG images based on Huang et al.’s method is proposed. Huang et al. embedded data into discrete cosine transform (DCT) coefficients with values 1 and − 1 (i.e., the selected coefficients) using histogram shifting. After analyzing the statistical properties of quantized DCT coefficient blocks of the JPEG images, it was concluded that the vast majority of blocks have no alternating current (AC) coefficients with values in (3, −3, 4, −4), especially when the quality factor (QF) is low. For these blocks, we propose a method which extends the selected coefficients with values in (1, −1) to values in (1, −1, 2, −2), then embeds secret data into the selected coefficients by doubling them, while keeping the unselected coefficients unchanged. The extended method can improve the embedding capacity as well as the image quality. For the other blocks, Huang’s method is still applied. Experimental results verify that the proposed scheme can achieve higher embedding capacity, while maintaining a similar image quality and file size as other schemes did.

Дослідження технології підготовки зображень із розширеним динамічним діапазоном для веб-сайтів

This work investigate the problem of the process of preparing high-dynamic range images (HDR-image) for hosting on websites. The proper functioning of websites it is necessary to take into account the effect of the large volume of HDR-image information. Therefore, the result of present research work will allow to determine the rational values of visual quality and file size of digital images, as well as to enhance the functionality of websites with HDR-image.According to the analysis of the previous research works of the technologies for the creation of HDR-photographs was determined of perspective directions of HDR-technologies: development of new effective image processing schemes, the creation of sensors in cameras with increased photosensitivity and the improvement of the devices design for the creation of HDR images.It was proposed the algorithm for the preparation of HDR-image with main steps: setting the camera and selecting rational modes (aperture, shutter speed and light sensitivity); preparation of the function of automatic change of exposure modes; receiving a series of RAW-images with different exposure indicators; the process of creating HDR-images using the Adobe Camera RAW utility.The Nikon D5100 camera and various photographic modes was used for capture RAW photos with various features (range of exposure compensation, exposure steps, and image compression). The evaluation of the relative quality index (the average value of contrast in 12 local gradation photo areas) was used to creating HDR-photos.According to the results of the research, the influence of the main modes and parameters of the process of creating images with an expanded dynamic range on the functionality of the site was established. The main recommendations for improving the websites functionality was developed.

Penerapan Metode End Of File Pada Steganografi Citra Gambar dengan Memanfaatkan Algoritma Affine Cipher sebagai Keamanan Pesan

The development of the world of information technology is very fast lately influential in all aspects of life. Kriprografi is a science based on mathematical techniques to deal with information security such as confidentiality, data integrity, and entity authentication. Affine Cipher or Affine password is a substitution cipher that is specifically for encryption or decryption per character. Therefore, Affine's password includes the stream cipher cryptographic algorithm. Steganography is a way of hiding the contents of a data in a cover of media or other digital data that cannot be predicted by ordinary people so as not to arouse suspicion from those who see it. The steganography image file has the same number of pixels as the original image file and there is no color difference between the two. The size of the steganography image file will increase, according to the length of the hidden message plus 6 bytes, in the form of 1 byte EOF and 5 byte message length. The End Of File (EOF) method is a technique for inserting data at the end of a file. When opened with a photo editor application, both images have the same pixel size, namely 240 x 238, and do not change color. In this test, what changes is the size of the image file, ie the initial size of the image is 49.132 bytes, changes to 49.145 bytes, or there is an addition of 13 bytes

Lossless Compression of Color Filter Array Mosaic Images With Visualization via JPEG 2000

Digital cameras have become ubiquitous for amateur and professional applications. The raw images captured by digital sensors typically take the form of color filter array (CFA) mosaic images, which must be (via digital signal processing) before they can be viewed. Photographers and scientists often repeat the using different parameters to obtain images suitable for different purposes. Since the development process is generally not invertible, it is commonly desirable to store the raw (or undeveloped) mosaic images indefinitely. Uncompressed mosaic image file sizes can be more than 30 times larger than those of developed images stored in JPEG format. Thus, data compression is of interest. Several compression methods for mosaic images have been proposed in the literature. However, they all require a custom decompressor followed by development-specific software to generate a displayable image. In this paper, a novel compression pipeline that removes these requirements is proposed. Specifically, mosaic images can be losslessly recovered from the resulting compressed files, and, more significantly, images can be directly viewed (decompressed and developed) using only a JPEG 2000 compliant image viewer. Experiments reveal that the proposed pipeline attains excellent visual quality, while providing compression performance competitive to that of state-of-the-art compression algorithms for mosaic images.

Leveraging content similarity among VMI files to allocate virtual machines in cloud

To meet a myriad of customers’ demands, a large number of virtual machines (VMs) have to be provisioned simultaneously in cloud data centers. Provisioning is usually time consuming due to the large size of virtual machine image (VMI) file that needs to be transferred via networks. To address this issue, researchers attempt to leverage the content similarity among different VMI files to reduce the volume of transferred data. In the VM provisioning, the VM packing problem that minimizes the number of physical machines is another important issue. In this paper, our goal is to find a solution that tries to pack VMs to the minimum number of PMs as well as significantly reduces the total amount of transferred data. We formally define the problem of VM packing and minimizing the data transferring in the VM provisioning, named RTVD-VA. We first propose an approximation algorithm to minimize the amount of transferred VMI data when provisioning K VMs with the same size to a single physical machine. We then extend the algorithm to address the scenario of multiple PMs when using the minimum number of PMs. Based on the above two approximation algorithms, we propose a heuristic algorithm, namely Balance-Placement, to solve the problem in general cases. Our simulation results show that Balance-Placement outperforms existing solutions like PSO and Greedy-Cache and achieves the least amount of transferred data and the minimum number of used PMs in most scenarios.

Evaluation of a confocal WSI scanner for FISH slide imaging and image analysis

Background: Technological advances contribute to the maturation of digital pathology in clinical and research applications. However, there are only few reports on fluorescence scanning especially on confocal fluorescence imaging technology in digital pathology, which has superior depth resolution compared to wide-field fluorescence imaging. Here, we explored the features of a confocal WSI scanner for typical diagnostic and research imaging applications of fluorescence in situ hybridization (FISH) assay.Methods: Multi-layer stacking (Z-stack) which stores all image information from each layer, and extended focus which stores the optimal image information from all scanned layers, featured in the Pannoramic Confocal scanner (3DHISTECH Ltd., Budapest, Hungary) were employed in digitizing 14 FISH slides (ALK, EGFR, and multi-gene). The slides were scanned with a 40× water immersion objective producing a final image with pixel resolution of 0.1625 µm/pixel. Z-stack and extended focus were used for N=6, 13, and 26 multiple layers scanning at 1, 0.4, and 0.2 µm depth intervals respectively. Single-layer scanning was also done for comparison. Scanning time and resultant file size were recorded. The CaseViewer from 3DHISTECH was used to visualize images and export the annotated regions, and the exported images were further analyzed in Imaris (Bitplane, Zurich, Switzerland) for 3-dimensional reconstruction, nuclear segmentation, and the quantification and co-localization analysis of dots inside nuclei. Quantification data from Imaris were imported into Excel for statistic analysis.Results: Confocal fluorescence scanning of FISH slides enabled sharper image than wide-field scanning, although it required longer scanning time and larger file storage. More intra-nuclear dots were quantified from multi-layer Z-stack images than single-layer images, and the Z-stack increased scanning time and image file size. Furthermore, there were a reduced in the number of dots and an increased in the number of co-localized dots in extended-focus images compared to Z-stack. Dots in multiple channels were quantified and analyzed automatically, which supports clinical diagnosis of gene amplification, deletion, and translocation. Three-dimensional reconstruction of Z-stack produced precise measurement of spatial distance, which supports molecular research.Conclusion: Confocal provides sharper image than wide-field for FISH slide scanning. Extended focus reduces file size and storage, but could cause inaccurate analysis due to misinterpretation of overlapping information. Z-stack scanning provides high volume image information for spatial analysis. We foresee confocal multi-layer scanning as a digital pathology application tool for FISH imaging in both clinical and research in future.

A small reduction in control tissue size yields a significant reduction in digital image storage cost

As digital pathology is becoming more prevalent, the cost of image storage becomes factor to consider. The purpose of this study was to test the effect of reducing the tissue size of frequently scanned slides on digital whole slide image file size and file storage cost. We investigated the file sizes of our most commonly scanned slides – the daily special stain controls. The average file size of these stains ranges from 109 to 476 MB. All of the Masson trichrome slides, Movat pentachrome slides, and PAS slides were reviewed from 2015, and the tissue measurements and file sizes were recorded. New, smaller control tissue blocks were created. Once scanned, the tissue measurements and file sizes were also recorded. Overall, we reduced the size of the tissue on the slide by an average of 74%. We calculate that for these three control tissues alone, $3465 in storage costs could be saved every year by reducing the size of the tissue on the slide.

Optimization of Image Compression algorithms using DWT- DCT method

Information is generated at very high speed in today’s Digital Era. Images have vast share in Information generated, so it’s important to reduce the image file size for storage and effective communication. Image compression technique helps in reducing storage and bandwidth requirement for transmission. Optimization of Image compression algorithms is the basic crux of this paper. DCT is most popularly used lossy image compression technique. It has disadvantage that at higher compression ratio the quality of image is lost. DCT is applied to set of images, followed by DWT. The resultant compression metrics are calculated and visual quality of image is analyzed. Experimental analysis shows reduction in storage space requirement and effective optimization using different methodology.

A remote display QoE improvement scheme for interactive applications in low network bandwidth environment

Screen transmission is an essential part of Desktop as a Service (DaaS) which directly influence the quality of experience (QoE). In this paper, we propose a novel QoE improvement scheme that dynamically controls the quality setting of the image compression before the screen transmission to decrease response time of the system still maintaining the satisfactory image quality, hence improves the QoE in interactive applications in a band-limited environment. The proposed scheme first selects the best quality setting appropriate for current network bandwidth quota, then uses the remaining bandwidth to improve the quality setting of low motion regions without any adverse effect on response time. To enable the adaptive quality selection and image quality refinement, we propose a compressed image file size inference model and a block priority calculation method respectively. Particularly, we implement our QoE Improvement Scheme to work with screen content coding. Both quantitative measurements and users’ evaluations in the experiments show that our QoE improvement scheme improves QoS as well as QoE by utilizing the available network bandwidth efficiently.

Multiple hypothesis colorization and its application to image compression

In this work we focus on the problem of colorization for image compression. Since color information occupies a large proportion of the total storage size of an image, a method that can predict accurate color from its grayscale version can produce a dramatic reduction in image file size. But colorization for compression poses several challenges. First, while colorization for artistic purposes simply involves predicting plausible chroma, colorization for compression requires generating output colors that are as close as possible to the ground truth. Second, many objects in the real world exhibit multiple possible colors. Thus, in order to disambiguate the colorization problem some additional information must be stored to reproduce the true colors with good accuracy. To account for the multimodal color distribution of objects we propose a deep tree-structured network that generates for every pixel multiple color hypotheses, as opposed to a single color produced by most prior colorization approaches. We show how to leverage the multimodal output of our model to reproduce with high fidelity the true colors of an image by storing very little additional information. In the experiments we show that our proposed method outperforms traditional JPEG color coding by a large margin, producing colors that are nearly indistinguishable from the ground truth at the storage cost of just a few hundred bytes for high-resolution pictures!

THE EFFECT OF JPEG COMPRESSION IN CLOSE RANGE PHOTOGRAMMETRY

Digital photogrammetry, using digital camera images, is an important low-cost engineering method to produce precise three-dimensional model of either an object or the part of the earth depending on the image quality. Photogrammetry which is cheaper and more practical than the new technologies such as LIDAR, has increased point cloud generation capacity during the past decade with contributions of computer vision. Images of new camera technologies needs huge storage space due to larger image file sizes. Moreover, this enormousness increases image process time during extraction, orientation and dense matching. The Joint Photographic Experts Group (JPEG) is one of the most commonly used methods as lossy compression standard for the storage purposes of the oversized image file. Particularly, image compression at different rates causes image deteriorations during the processing period. Therefore, the compression rates affect accuracy of photogrammetric measurements. In this study, the close range images compressed at the different levels were investigated to define the compression effect on photogrammetric results, such as orientation parameters and 3D point cloud. The outcomes of this study show that lower compression ratios are acceptable in photogrammetric process when moderate accuracy is sufficient.

A Non-format Compliant Scalable RSA-based JPEG Encryption Algorithm

A non-format compliant JPEG encryption algorithm is proposed which is based on a modification of the RSA encryption system. Firstly, an alternate form of entropy coding is described, which is more suited to the proposed algorithm, instead of the zigzag coding scheme used in JPEG. The algorithm for the encryption and decryption process is then elaborated. A variant of the algorithm, also based on the RSA algorithm is also described, which is faster than the original algorithm, but expands the bit stream slightly. Both the algorithms are shown to be scalable and resistant to ‘sketch’ attacks. Finally, the encrypted file sizes for both the algorithms are compared with the unencrypted JPEG compressed image file size. The encrypted image is found to be moderately expanded, but which is justified by the high security and most importantly, the scalability of the algorithm.

A Compressed Brain Image Classification System Enhance with Multi Image Particle Swarm Optimization Segmentation

Compression methods reduce the file size of images through the reduction of data required for representing images that are similar to the original by way or removing redundancies. Smart cards possess embedded integrated circuits comprising memory as well as micro-processing components. Images regarding the card holder's medical history, fingerprints, palm print and so on are stored. Multi-application smart cards are rapidly becoming the replacement for traditional cards like driving license, identity cards, credit cards and so on as a single card. Hence, the quantity of information in storage within one card is great, which requires techniques for compressing the data so that the card may be effectively used. Images are segmented through extension of active contour models for finding image contours through the suggested Multi Image Particle Swarm Optimization (MI-PSO).

Commentary: Can pathologists interpret digital images as well as they interpret microscope slides?

Commentary: Can pathologists interpret digital images as well as they interpret microscope slides?

Evaluation of panoramic digital images using Panoptiq for frozen section diagnosis

Introduction: Whole slide imaging (WSI) permits intraoperative consultations (frozen sections) to be performed remotely. However, WSI files are large and can be problematic if there are tissue artifacts (e.g., tissue folds) or when slides are scanned without multiplanes (Z-stacks) to permit focusing. The Panoptiq dynamic imaging system allows users to create their own digital files that combine low power panoramic digital images with regions of interest that can be imaged using high power Z-stacks. The aim of this study was to determine the utility of the Panoptiq dynamic imaging system for frozen section telepathology. Materials and Methods: Twenty archival randomly selected genitourinary surgical pathology frozen sectional cases were evaluated using conventional light microscopy (glass slides), panoramic images, and whole slide images. To create panoramic images glass slides were digitized using a Prosilica GT camera (model GT1920C, Allied Vision Technologies) attached to an Olympus B × 45 microscope and Dell Precision Tower 810 computer (Dell). Panoptiq 3 version 3.1.2 software was used for image acquisition and Panoptiq View version 3.l.2 to view images (ViewsIQ, Richmond, BC, Canada). Image acquisition using Panoptiq software involved a pathology resident, who manually created digital maps (×4 objective) and then selected representative regions of interest to generate Z-stacks at higher magnification (×40 objective). Whole slide images were generated using an Aperio XT Scanscope (Leica) and viewed using ImageScope Software (Aperio ePathology, Leica). Three pathologists were asked to render diagnoses and rate image quality (1–10) and their diagnostic confidence (1–10) for each modality. Results: The diagnostic concordance with glass slides was 98.3% for panoramic images and 100% for WSI. Panoptiq images were comparable to the glass slide viewing experience in terms of image quality and diagnostic confidence. Complaints regarding WSI included poor focus near tissue folds and air bubbles. Panoptiq permitted fine focusing of tissue folds and air bubbles. Issues with panoramic images included difficulty interpreting low-resolution ×4 image maps and the presence of tiling artifacts. In some cases, Z-stacked areas of Panoptiq images were limited or not representative of diagnostic regions. The image file size of Panoptiq was more than 14 times smaller than that of WSI files. Conclusions: The Panoptiq imaging system is a novel tool that can be used for frozen section telepathology. Panoramic digital images were easy to generate and navigate, of relatively small file size, and offered a mechanism to overcome focusing problems commonly encountered with WSI of frozen sections. However, the acquisition of representative Panoptiq images was operator dependent with the individual creating files that may impact the final diagnosis.

USING PARAMETERS OF DYNAMIC PULSE FUNCTION FOR 3D MODELING IN LOD3 BASED ON RANDOM TEXTURES

Abstract. The pulse function (PF) is a technique based on procedural preprocessing system to generate a computerized virtual photo of the façade with in a fixed size square(Alizadehashrafi et al., 2009, Musliman et al., 2010). Dynamic Pulse Function (DPF) is an enhanced version of PF which can create the final photo, proportional to real geometry. This can avoid distortion while projecting the computerized photo on the generated 3D model(Alizadehashrafi and Rahman, 2013). The challenging issue that might be handled for having 3D model in LoD3 rather than LOD2, is the final aim that have been achieved in this paper. In the technique based DPF the geometries of the windows and doors are saved in an XML file schema which does not have any connections with the 3D model in LoD2 and CityGML format. In this research the parameters of Dynamic Pulse Functions are utilized via Ruby programming language in SketchUp Trimble to generate (exact position and deepness) the windows and doors automatically in LoD3 based on the same concept of DPF. The advantage of this technique is automatic generation of huge number of similar geometries e.g. windows by utilizing parameters of DPF along with defining entities and window layers. In case of converting the SKP file to CityGML via FME software or CityGML plugins the 3D model contains the semantic database about the entities and window layers which can connect the CityGML to MySQL(Alizadehashrafi and Baig, 2014). The concept behind DPF, is to use logical operations to project the texture on the background image which is dynamically proportional to real geometry. The process of projection is based on two vertical and horizontal dynamic pulses starting from upper-left corner of the background wall in down and right directions respectively based on image coordinate system. The logical one/zero on the intersections of two vertical and horizontal dynamic pulses projects/does not project the texture on the background image. It is possible to define priority for each layer. For instance the priority of the door layer can be higher than window layer which means that window texture cannot be projected on the door layer. Orthogonal and rectified perpendicular symmetric photos of the 3D objects that are proportional to the real façade geometry must be utilized for the generation of the output frame for DPF. The DPF produces very high quality and small data size of output image files in quite smaller dimension compare with the photorealistic texturing method. The disadvantage of DPF is its preprocessing method to generate output image file rather than online processing to generate the texture within the 3D environment such as CityGML. Furthermore the result of DPF can be utilized for 3D model in LOD2 rather than LOD3. In the current work the random textures of the window layers are created based on parameters of DPF within Ruby console of SketchUp Trimble to generate the deeper geometries of the windows and their exact position on the façade automatically along with random textures to increase Level of Realism (LoR)(Scarpino, 2010). As the output frame in DPF is proportional to real geometry (height and width of the façade) it is possible to query the XML database and convert them to units such as meter automatically. In this technique, the perpendicular terrestrial photo from the façade is rectified by employing projective transformation based on the frame which is in constrain proportion to real geometry. The rectified photos which are not suitable for texturing but necessary for measuring, can be resized in constrain proportion to real geometry before measuring process. Height and width of windows, doors, horizontal and vertical distance between windows from upper left corner of the photo dimensions of doors and windows are parameters that should be measured to run the program as a plugins in SketchUp Trimble. The system can use these parameters and texture file names and file paths to create the façade semi-automatically. To avoid leaning geometry the textures of windows, doors and etc, should be cropped and rectified from perpendicular photos, so that they can be used in the program to create the whole façade along with its geometries. Texture enhancement should be done in advance such as removing disturbing objects, exposure setting, left-right up-down transformation, and so on. In fact, the quality, small data size, scale and semantic database for each façade are the prominent advantages of this method.

Performance based Analysis of Wavelets Family for Image Compression-A Practical Approach

Image compression has become vital in today‟s scenario because lots of digital images has become spread over the servers which uses lots of space. The size of image files increased in the past 15 years due to the rapid technological advancement and increasing quality of images. In such conditions, it has become significant to use an efficient algorithm to compress images in such a manner so that it gives better compression with minimum loss in quality with respect to different quality measures. The proposed image compression method is implemented in frequency domain using wavelet transform. In this paper, Haar, Symlet, Coiflets, reverse biorthogonal, biorthogonal, and Daubechies wavelets are analyzed for the compression. There are mother wavelets, each of them is analyzed with respect to image compression scheme and resulting wavelets are given as the output which wavelets are resulting in goodcompression.

A method for quantitative analysis of clump thickness in cervical cytology slides

Knowledge of the spatial distribution and thickness of cytology specimens is critical to the development of digital slide acquisition techniques that minimise both scan times and image file size. In this paper, we evaluate a novel method to achieve this goal utilising an exhaustive high-resolution scan, an over-complete wavelet transform across multi-focal planes and a clump segmentation of all cellular materials on the slide. The method is demonstrated with a quantitative analysis of ten normal, but difficult to scan Pap stained, Thin-prep, cervical cytology slides. We show that with this method the top and bottom of the specimen can be estimated to an accuracy of 1μm in 88% and 97% of the fields of view respectively. Overall, cellular material can be over 30μm thick and the distribution of cells is skewed towards the cover-slip (top of the slide). However, the median clump thickness is 10μm and only 31% of clumps contain more than three nuclei. Therefore, by finding a focal map of the specimen the number of 1μm spaced focal planes that are required to be scanned to acquire 95% of the in-focus material can be reduced from 25.4 to 21.4 on average. In addition, we show that by considering the thickness of the specimen, an improved focal map can be produced which further reduces the required number of 1μm spaced focal planes to 18.6. This has the potential to reduce scan times and raw image data by over 25%.